principles of programming and problem solving notes

What is Programming? A Handbook for Beginners

Welcome to the amazing world of programming. This is one of the most useful and powerful skills that you can learn and use to make your visions come true.

In this handbook, we will dive into why programming is important, its applications, its basic concepts, and the skills you need to become a successful programmer.

You will learn:

• What programming is and why it is important .
• What a programming language is and why it is important .
• How programming is related to binary numbers .
• Real-world applications of programming .
• Skills you need to succeed as a programmer .
• Tips for learning how to code .
• Basic programming concepts .
• Types of programming languages .
• How to contribute to open source projects .
• And more...

Are you ready? Let's begin! ✨  

🔹 What is Programming?

Did you know that computer programming is already a fundamental part of your everyday lives? Let's see why. I'm sure that you will be greatly surprised.

Every time you turn on your smartphone, laptop, tablet, smart TV, or any other electronic device, you are running code that was planned, developed, and written by developers. This code creates the final and interactive result that you can see on your screen.

That is exactly what programming is all about. It is the process of writing code to solve a particular problem or to implement a particular task.

Programming is what allows your computer to run the programs you use every day and your smartphone to run the apps that you love. It is an essential part of our world as we know it.

Whenever you check your calendar, attend virtual conferences, browse the web, or edit a document, you are using code that has been written by developers.

"And what is code?" you may ask.

Code is a sequence of instructions that a programmer writes to tell a device (like a computer) what to do.

The device cannot know by itself how to handle a particular situation or how to perform a task. So developers are in charge of analyzing the situation and writing explicit instructions to implement what is needed.

To do this, they follow a particular syntax (a set of rules for writing the code).

A developer (or programmer) is the person who analyzes a problem and implements a solution in code.

Sounds amazing, right? It's very powerful and you can be part this wonderful world too by learning how to code. Let's see how.

You, as a developer.

Let's put you in a developer's shoes for a moment. Imagine that you are developing a mobile app, like the ones that you probably have installed on your smartphone right now.

What is the first thing that you would do?

Think about this for a moment.

The answer is...

Analyzing the problem. What are you trying to build?

As a developer, you would start by designing the layout of the app, how it will work, its different screens and functionality, and all the small details that will make your app an awesome tool for users around the world.

Only after you have everything carefully planned out, you can start to write your code. To do that, you will need to choose a programming language to work with. Let's see what a programming language is and why they are super important.

🔸 What is a Programing Language?

A programming language is a language that computers can understand.

We cannot just write English words in our program like this:

"Computer, solve this task!"

and hope that our computer can understand what we mean. We need to follow certain rules to write the instructions.

Every programming language has its own set of rules that determine if a line of code is valid or not. Because of this, the code you write in one programming language will be slightly different from others.

💡 Tip: Some programming languages are more complex than others but most of them share core concepts and functionality. If you learn how to code in one programming language, you will likely be able to learn another one faster.

Before you can start writing awesome programs and apps, you need to learn the basic rules of the programming language you chose for the task.

💡 Tip: a program is a set of instructions written in a programming language for the computer to execute. We usually write the code for our program in one or multiple files.

For example, this is a line of code in Python (a very popular programming language) that shows the message "Hello, World!" :

But if we write the same line of code in JavaScript (a programming language mainly used for web development), we will get an error because it will not be valid.

To do something very similar in JavaScript, we would write this line of code instead:

Visually, they look very different, right? This is because Python and JavaScript have a different syntax and a different set of built-in functions .

💡 Tip : built-in functions are basically tasks that are already defined in the programming language. This lets us use them directly in our code by writing their names and by specifying the values they need.  

In our examples, print() is a built-in function in Python while console.log() is a function that we can use in JavaScript to see the message in the console (an interactive tool) if we run our code in the browser.

Examples of programming languages include Python, JavaScript, TypeScript, Java, C, C#, C++, PHP, Go, Swift, SQL, and R. There are many programming languages and most of them can be used for many different purposes.

💡 Tip: These were the most popular programming languages on the Stack Overflow Developer Survey 2022 :

There are many other programming languages (hundreds or even thousands!) but usually, you will learn and work with some of the most popular ones. Some of them have broader applications like Python and JavaScript while others (like R) have more specific (and even scientific) purposes.

This sounds very interesting, right? And we are only starting to talk about programming languages. There is a lot to learn about them and I promise you that if you dive deeper into programming, your time and effort will be totally worth it.

Awesome! Now that you know what programming is and what programming languages are all about, let's see how programming is related to binary numbers.

🔹 Programming and Binary Numbers

When you think about programming, perhaps the first thing that comes to your mind is something like the below image, right? A sequence of 0 s and 1 s on your computer.

Programming is indeed related to binary numbers ( 0 and 1 ) but in an indirect way. Developers do not actually write their code using zeros and ones.

We usually write programs in a high-level programming language, a programming language with a syntax that recognizes specific words (called keywords), symbols, and values of different data types.

Basically, we write code in a way that humans can understand.

For example, these are the keywords that we can use in Python:

Every programming language has its own set of keywords (words written in English). These keywords are part of the syntax and core functionality of the programming language.

But keywords are just common words in English, almost like the ones that we would find in a book.

That leads us to two very important questions:

• How does the computer understand and interpret what we are trying to say?
• Where does the binary number system come into play here?

The computer does not understand these words, symbols, or values directly.

When a program runs, the code that we write in a high-level programming language that humans can understand is automatically transformed into binary code that the computer can understand.

This transformation of source code that humans can understand into binary code that the computer can understand is called compilation .

According to Britannica , a compiler is defined as:

Computer software that translates (compiles) source code written in a high-level language (e.g., C++) into a set of machine-language instructions that can be understood by a digital computer’s CPU.

Britannica also mentions that:

The term compiler was coined by American computer scientist Grace Hopper , who designed one of the first compilers in the early 1950s.

Some programming languages can be classified as compiled programming languages while others can be classified as interpreted programming languages based on how to they are transformed into machine-language instructions.

However, they all have to go through a process that converts them into instructions that the computer can understand.

Awesome. Now you know why binary code is so important for computer science. Without it, basically programming would not exist because computers would not be able to understand our instructions.

Now let's dive into the applications of programming and the different areas that you can explore.

🔸 Real-World Applications of Programming

Programming has many different applications in many different industries. This is truly amazing because you can apply your knowledge in virtually any industry that you are interested in.

From engineering to farming, from game development to physics, the possibilities are endless if you learn how to code.  

Let's see some of them. (I promise you. They are amazing! ⭐) .

Front-End Web Development

If you learn how to code, you can use your programming skills to design and develop websites and online platforms. Front-End Web Developers create the parts of the websites that users can see and interact with directly.

For example, right now you are reading an article on freeCodeCamp 's publication. The publication looks like this and it works like this thanks to code that front-end web developers wrote line by line.

💡 Tip: If you learn front-end web development, you can do this too.

Front-End Web Developers use HTML and CSS to create the structure of the website (these are markup languages, which are used to present information) and they write JavaScript code to add functionality and interactivity.

If you are interested in learning front-end web development, you can learn HTML and CSS with these free courses on freeCodeCamp's YouTube Channel:

• Learn HTML5 and CSS3 From Scratch - Full Course
• Learn HTML & CSS – Full Course for Beginners
• Frontend Web Development Bootcamp Course (JavaScript, HTML, CSS)
• Introduction To Responsive Web Design - HTML & CSS Tutorial

You can also learn JavaScript for free with these free online courses:

• Learn JavaScript - Full Course for Beginners
• JavaScript Programming - Full Course
• JavaScript DOM Manipulation – Full Course for Beginners
• Learn JavaScript by Building 7 Games - Full Course

💡 Tip: You can also earn a Responsive Web Design Certification while you learn with interactive exercises on freeCodeCamp.

Back-End Web Development

More complex and dynamic web applications that work with user data also require a server . This is a computer program that receives requests and sends appropriate responses. They also need a database , a collection of values stored in a structured way.

Back-End Web Developers are in charge of developing the code for these servers. They decide how to handle the different requests, how to send appropriate resources, how to store the information, and basically how to make everything that runs behind the scenes work smoothly and efficiently.

A real-world example of back-end web development is what happens when you create an account on freeCodeCamp and complete a challenge. Your information is stored on a database and you can access it later when you sign in with your email and password.

This amazing interactive functionality was implemented by back-end web developers.

💡 Tip: Full-stack Web Developers are in charge of both Front-End and Back-End Web Development. They have specialized knowledge on both areas.

All the complex platforms that you use every day, like social media platforms, online shopping platforms, and educational platforms, use servers and back-end web development to power their amazing functionality.

Python is an example of a powerful programming language used for this purpose. This is one of the most popular programming languages out there, and its popularity continues to rise every year. This is partly because it is simple and easy to learn and yet powerful and versatile enough to be used in real-world applications.

💡 Tip: if you are curious about the specific applications of Python, this is an article I wrote on this topic .

JavaScript can also be used for back-end web development thanks to Node.js.

Other programming languages used to develop web servers are PHP, Ruby, C#, and Java.

If you would like to learn Back-End Web Development, these are free courses on freeCodeCamp's YouTube channel:

• Python Backend Web Development Course (with Django)
• Node.js and Express.js - Full Course
• Full Stack Web Development for Beginners (Full Course on HTML, CSS, JavaScript, Node.js, MongoDB)
• Node.js / Express Course - Build 4 Projects

💡 Tip: freeCodeCamp also has a free Back End Development and APIs certification.

Mobile App Development

Mobile apps have become part of our everyday lives. I'm sure that you could not imagine life without them.

Think about your favorite mobile app. What do you love about it?

Our favorite apps help us with our daily tasks, they entertain us, they solve a problem, and they help us to achieve our goals. They are always there for us.

That is the power of mobile apps and you can be part of this amazing world too if you learn mobile app development.

Developers focused on mobile app development are in charge of planning, designing, and developing the user interface and functionality of these apps. They identify a gap in the existing apps and they try to create a working product to make people's lives better.

💡 Tip: regardless of the field you choose, your goal as a developer should always be making people's lives better. Apps are not just apps, they have the potential to change our lives. You should always remember this when you are planning your projects. Your code can make someone's life better and that is a very important responsibility.

Mobile app developers use programming languages like JavaScript, Java, Swift, Kotlin, and Dart. Frameworks like Flutter and React Native are super helpful to build cross-platform mobile apps (that is, apps that run smoothly on multiple different operating systems like Android and iOS).

According to Flutter 's official documentation:

Flutter is an open source framework by Google for building beautiful, natively compiled, multi-platform applications from a single codebase.

If you would like to learn mobile app development, these are free courses that you can take on freeCodeCamp's YouTube channel:

• Flutter Course for Beginners – 37-hour Cross Platform App Development Tutorial
• Flutter Course - Full Tutorial for Beginners (Build iOS and Android Apps)
• React Native - Intro Course for Beginners
• Learn React Native Gestures and Animations - Tutorial

Game Development

Games create long-lasting memories. I'm sure that you still remember your favorite games and why you love (or loved) them so much. Being a game developer means having the opportunity of bringing joy and entertainment to players around the world.

Game developers envision, design, plan, and implement the functionality of a game. They also need to find or create assets such as characters, obstacles, backgrounds, music, sound effects, and more.

💡 Tip: if you learn how to code, you can create your own games. Imagine creating an awesome and engaging game that users around the world will love. That is what I personally love about programming. You only need your computer, your knowledge, and some basic tools to create something amazing.

Popular programming languages used for game development include JavaScript, C++, Python, and C#.

If you are interested in learning game development, you can take these free courses on freeCodeCamp's YouTube channel:

• JavaScript Game Development Course for Beginners
• Learn Unity - Beginner's Game Development Tutorial
• Learn Python by Building Five Games - Full Course
• Code a 2D Game Using JavaScript, HTML, and CSS (w/ Free Game Assets) – Tutorial
• 2D Game Development with GDevelop - Crash Course
• Pokémon Coding Tutorial - CS50's Intro to Game Development

Biology, Physics, and Chemistry

Programming can be applied in every scientific field that you can imagine, including biology, physics, chemistry, and even astronomy. Yes! Scientists use programming all the time to collect and analyze data. They can even run simulations to test hypotheses.

In biology, computer programs can simulate population genetics and population dynamics. There is even an entire field called bioinformatics .

According to this article "Bioinformatics" by Ardeshir Bayat, member of the Centre for Integrated Genomic Medical Research at the University of Manchester:

Bioinformatics is defined as the application of tools of computation and analysis to the capture and interpretation of biological data.

Dr. Bayat mentions that bioinformatics can be used for genome sequencing. He also mentions that its discoveries may lead to drug discoveries and individualized therapies.

Frequently used programming languages for bioinformatics include Python, R, PHP, PERL, and Java.

💡 Tip: R is a programming "language and environment for statistical computing and graphics" ( source ).

An example of a great tool that scientists can use for biology is Biopython . This is a Python framework with "freely available tools for biological computation."

If you would like to learn more about how you can apply your programming skills in science, these are free courses that you can take on freeCodeCamp's YouTube channel:

• Python for Bioinformatics - Drug Discovery Using Machine Learning and Data Analysis
• R Programming Tutorial - Learn the Basics of Statistical Computing
• Learn Python - Full Course for Beginners [Tutorial]

Physics requires running many simulations and programming is perfect for doing exactly that. With programming, scientists can program and run simulations based on specific scenarios that would be hard to replicate in real life. This is much more efficient.

Programming languages that are commonly used for physics simulations include C, Java, Python, MATLAB, and JavaScript.  

Chemistry also relies on simulations and data analysis, so it's a field where programming can be a very helpful tool.

In this scientific article by Dr. Ivar Ugi and his colleagues from Organisch-chemisches Institut der Technischen Universität München, they mention that:

The design of entirely new syntheses, and the classification and documentation of structures, substructures, and reactons are examples of new applications of computers to chemistry.

Scientific experiments also generate detailed data and results that can be analyzed with computer programs developed by scientists.  

Think about it: writing a program to generate a box plot or a scatter plot or any other type of plot to visualize trends in thousands of measurements can save researchers a lot of time and effort. This lets them focus on the most important part of their work: analyzing the results.

💡 Tips: if you are interested in diving deeper into this, this is a list of chemistry simulations by the American Chemical Society. These simulations were programmed by developers and they are helping thousands of students and teachers around the world.

Think about it...You could build the next great simulation. If you are interested in a scientific field, I totally recommend learning how to code. Your work will be much more productive and your results will be easier to analyze.

If you are interested in learning programming for scientific applications, these are free courses on freeCodeCamp's YouTube channel:

• Python for Data Science - Course for Beginners (Learn Python, Pandas, NumPy, Matplotlib)

Data Science and Engineering

Talking about data...programming is also essential for a field called Data Science . If you are interested in answering questions through data and statistics, this field might be exactly what you are looking for and having programming skills will help you to achieve your goals.

Data scientists collect and analyze data in order to answer questions in many different fields. According to UC Berkeley in the article " What is Data Science? ":

Effective data scientists are able to identify relevant questions, collect data from a multitude of different data sources, organize the information, translate results into solutions, and communicate their findings in a way that positively affects business decisions.

There are many powerful programming languages for analyzing and visualizing data, but perhaps one of the most frequently used ones for this purpose is Python.

This is an example of the type of data visualizations that you can create with Python. They are very helpful to analyze data visually and you can customize them to your fit needs.

If you are interested in learning programming for data science, these are free courses on freeCodeCamp's YouTube channel:

• Learn Data Science Tutorial - Full Course for Beginners
• Intro to Data Science - Crash Course for Beginners
• Build 12 Data Science Apps with Python and Streamlit - Full Course
• Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn)

💡 Tip: you can also earn these free certifications on freeCodeCamp:

• Data Visualization
• Data Analysis with Python

Engineering

Engineering is another field where programming can help you to succeed. Being able to write your own computer programs can make your work much more efficient.

There are many tools created specifically for engineers. For example, the R programming language is specialized in statistical applications and Python is very popular in this field too.

Another great tool for programming in engineering is MATLAB . According to its official website:

MATLAB is a programming and numeric computing platform used by millions of engineers and scientists to analyze data, develop algorithms, and create models.

Really, the possibilities are endless.

You can learn MATLAB with this crash course on the freeCodeCamp YouTube channel .

If you are interested in learning engineering tools related to programming, this is a free course on freeCodeCamp's YouTube channel that covers AutoCAD, a 2D and 3D computer-aided design software used by engineers:

• AutoCAD for Beginners - Full University Course

Medicine and Pharmacology

Medicine and pharmacology are constantly evolving by finding new treatments and procedures. Let's see how you can apply your programming skills in these fields.

Programming is really everywhere. If you are interested in the field of medicine, learning how to code can be very helpful for you too. Even if you would like to focus on computer science and software development, you can apply your knowledge in both fields.

Specialized developers are in charge of developing and writing the code that powers and controls the devices and machines that are used by modern medicine.

Think about it...all these machines and devices are controlled by software and someone has to write that software. Medical records are also stored and tracked by specialized systems created by developers. That could be you if you decide to follow this path. Sounds exciting, right?

According to the scientific article Application of Computer Techniques in Medicine :

Major uses of computers in medicine include hospital information system, data analysis in medicine, medical imaging laboratory computing, computer assisted medical decision making, care of critically ill patients, computer assisted therapy and so on.

Pharmacology

Programming and computer science can also be applied to develop new drugs in the field of pharmacology.

A remarkable example of what you can achieve in this field by learning how to code is presented in this article by MIT News. It describes how an MIT senior, Kristy Carpenter, was using computer science in 2019 to develop "new, more affordable drugs." Kristy mentions that:

Artificial intelligence, which can help compute the combinations of compounds that would be better for a particular drug, can reduce trial-and-error time and ideally quicken the process of designing new medicines.

Another example of a real-world application of programming in pharmacology is related to Python (yes, Python has many applications!). Among its success stories , we find that Python was selected by AstraZeneca to develop techniques and programs that can help scientists to discover new drugs faster and more efficiently.

The documentation explains that:

To save time and money on laboratory work, experimental chemists use computational models to narrow the field of good drug candidates, while also verifying that the candidates to be tested are not simple variations of each other's basic chemical structure.

If you are interested in learning programming for medicine or health-related fields, this is a free course on freeCodeCamp's YouTube channel on programming for healthcare imaging:

• PyTorch and Monai for AI Healthcare Imaging - Python Machine Learning Course

Have you ever thought that programming could be helpful for education? Well, let me tell you that it is and it is very important. Why? Because the digital learning tools that students and teachers use nowadays are programmed by developers.

Every time a student opens an educational app, browses an educational platform like freeCodeCamp, writes on a digital whiteboard, or attends a class through an online meeting platform, programming is making that possible.

As a programmer or as a teacher who knows how to code, you can create the next great app that will enhance the learning experience of students around the world.

Perhaps it will be a note-taking app, an online learning platform, a presentation app, an educational game, or any other app that could be helpful for students.

The important thing is to create it with students in mind if your goal is to make something amazing that will create long-lasting memories.

If you envision it, then you can create it with code.  

Teachers can also teach their students how to code to develop their problem-solving skills and to teach them important skills for their future.

💡 Tip: if you are teaching students how to code, Scratch is a great programming language to teach the basics of programming. It is particularly focused on teaching children how to code in an interactive way.

According to the official Scratch website:

Scratch is the world’s largest coding community for children and a coding language with a simple visual interface that allows young people to create digital stories, games, and animations.

If you are interested in learning how to code for educational purposes, these are courses that you may find helpful on freeCodeCamp's YouTube channel:

• Scratch Tutorial for Beginners - Make a Flappy Bird Game
• Computational Thinking & Scratch - Intro to Computer Science - Harvard's CS50 (2018)
• Android Development for Beginners - Full Course

Machine Learning, Artificial Intelligence, and Robotics

Some of the most amazing fields that are directly related to programming are Machine Learning, Artificial Intelligence, and Robotics. Let's see why.

Artificial Intelligence is defined by Britannica as:

The project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.

Machine learning is a branch or a subset of the field of Artificial Intelligence in which systems can learn on their own based on data. The goal of this learning process is to predict the expected output. These models continuously learn how to "think" and how to analyze situations based on their previous training.

The most commonly used programming languages in these fields are Python, C, C#, C++, and MATLAB.

Artificial intelligence and Machine Learning have amazing applications in various industries, such as:

• Image and object detection.
• Making predictions based on patterns.
• Text recognition.
• Recommendation engines (like when an online shopping platform shows you products that you may like or when YouTube shows you videos that you may like).
• Spam detection for emails.
• Fraud detection.
• Social media features like personalized feeds.
• Many more... there are literally millions of applications in virtually every industry.

If you are interested in learning how to code for Artificial Intelligence and Machine Learning, these are free courses on freeCodeCamp's YouTube channel:

• Machine Learning for Everybody – Full Course
• Machine Learning Course for Beginners
• PyTorch for Deep Learning & Machine Learning – Full Course
• TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
• Self-Driving Car with JavaScript Course – Neural Networks and Machine Learning
• Python TensorFlow for Machine Learning – Neural Network Text Classification Tutorial
• Practical Deep Learning for Coders - Full Course from fast.ai and Jeremy Howard
• Deep Learning Crash Course for Beginners
• Advanced Computer Vision with Python - Full Course

💡 Tip: you can also earn a Machine Learning with Python Certification on freeCodeCamp.

Programming is also very important for robotics. Yes, robots are programmed too!

Robotics is defined by Britannica as the:

Design, construction, and use of machines (robots) to perform tasks done traditionally by human beings.

Robots are just like computers. They do not know what to do until you tell them what to do by writing instructions in your programs. If you learn how to code, you can program robots and industrial machinery found in manufacturing facilities.

If you are interested in learning how to code for robotics, electronics, and related fields, this is a free course on Arduino on freeCodeCamp's YouTube channel:

• Arduino Course for Beginners - Open-Source Electronics Platform

Other Applications

There are many other fascinating applications of programming in almost every field. These are some highlights:

• Agriculture: in this article by MIT News, a farmer developed an autonomous tractor app after learning how to code.
• Self-driving cars: autonomous cars rely on software to analyze their surroundings and to make quick and accurate decisions on the road. If you are interested in this area, this is a course on this topic on freeCodeCamp's YouTube channel.
• Finance: programming can also be helpful to develop programs and models that predict financial indicators and trends. For example, this is a course on algorithmic trading on freeCodeCamp's YouTube channel.

The possibilities are endless. I hope that this section will give you a notion of why learning how to code is so important for your present and for your future. It will be a valuable skill to have in any field you choose.

Awesome. Now let's dive into the soft skills that you need to become a successful programmer.

🔹 Skills of a Successful Programmer

After going through the diverse range of applications of programming, you must be curious to know what skills are needed to succeed in this field.

A programmer should be curious. Whether you are just starting to learn how to code or you already have 20 years of experience, coding projects will always present you with new challenges and learning opportunities. If you take these opportunities, you will continously improve your skills and succeed.

Enthusiasm is a key trait of a successful programmer but this applies in general to any field if you want to succeed. Enthusiasm will keep you happy and curious about what you are creating and learning.

💡 Tip: If you ever feel like you are not as enthusiastic as you used to be, it's time to find or learn something new that can light the spark in you again and fill you with hope and dreams.

A programmer must be patient because transforming an initial idea into a working product can take time, effort, and many different steps. Patience will keep you focused on your final goal.  

Programming can be challenging. That is true. But what defines you is not how many challenges you face, it's how you face them. If you thrive despite these challenges, you will become a better programmer and you could create something that could change the world.

Programmers must be creative because even though every programming language has a particular set of rules for writing the code, coding is like using LEGOs. You have the building-blocks but you need to decide what to create and how to create it. The process of writing the code requires creativity while following the established best practices.

Problem-solving and Analysis

Programming is basically analyzing and solving problems with code. Depending on your field of choice, those problems will be simpler or more complex but they will all require some level of problem-solving skills and a thorough analysis of the situation.

Questions like:

• What should I build?
• How can I build it?
• What is the best way to build this?

Are part of the everyday routine of a programmer.

Ability to Focus for Long Periods of Time

When you are working on a coding project, you will need to focus on a task for long periods of time. From creating the design, to planning and writing the code, to testing the result, and to fixing bugs (issues with the code), you will dedicate many hours to a particular task. This is why it's essential to be able to focus and to keep your final goal in mind.

Taking Detailed Notes

This skill is very important for programmers, particularly when you are learning how to code. Taking detailed notes can be help you to understand and remember the concepts and tools you learn. This also applies for experienced programmers, since being a programmer involves life-long learning.

Communication

Initially, you might think that programming is a solitary activity and imagine that a programmer spends hundreds of hours alone sitting on a desk.

But the reality is that when you find your first job, you will see that communication is super important to coordinate tasks with other team members and to exchange ideas and feedback.

Open to Feedback

In programming, there is usually more than one way to implement the same functionality. Different alternatives may work similarly, but some may be easier to read or more efficient in terms of time or resource consumption.

When you are learning how to code, you should always take constructive feedback as a tool for learning. Similarly, when you are working on a team, take your colleagues' feedback positively and always try to improve.

Life-long Learning

Programming equals life-long learning. If you are interested in learning how to code, you must know that you will always need to be learning new things as new technologies emerge and existing technologies are updated. Think about it... that is great because there is always something interesting and new to learn!

Open to Trying New Things

Finally, an essential skill to be a successful programmer is to be open to trying new things. Step out of your comfort zone and be open to new technologies and products. In the technology industry, things evolve very quickly and adapting to change is essential.

🔸 Tips for Learning How to Code

Now that you know more about programming, programming languages, and the skills you need to be a successful programmer, let's see some tips for learning how to code.

💡 Tip: these tips are based on my personal experience and opinions.

• Choose one programming language to learn first. When you are learning how to code, it's easy to feel overwhelmed with the number of options and entry paths. My advice would be to focus on understanding the essential computer science concepts and one programming language first. Python and JavaScript are great options to start learning the fundamentals.
• Take detailed notes. Note-taking skills are essential to record and to analyze the topics you are learning. You can add custom comments and annotations to explain what you are learning.
• Practice constantly. You can only improve your problem-solving skills by practicing and by learning new techniques and tools. Try to practice every day.

💡 Tip: There is a challenge called the #100DaysOfCode challenge that you can join to practice every day.  

• Always try again. If you can't solve a problem on your first try, take a break and come back again and again until you solve it. That is the only way to learn. Learn from your mistakes and learn new approaches.
• Learn how to research and how to find answers. Programming languages, libraries, and frameworks usually have official documentations that explain their built-in elements and tools and how you can use them. This is a precious resource that you should definitely refer to.
• Browse Stack Overflow . This is an amazing platform. It is like an online encyclopedia of answers to common programming questions. You can find answers to existing questions and ask new questions to get help from the community.
• Set goals. Motivation is one of the most important factors for success. Setting goals is very important to keep you focused, motivated, and enthusiastic. Once you reach your goals, set new ones that you find challenging and exciting.
• Create projects. When you are learning how to code, applying your skills will help you to expand your knowledge and remember things better. Creating projects is the perfect way to practice and to create a portfolio that you can show to potential employers.

🔹 Basic Programming Concepts

Great. If reading this article has helped you confirm that you want to learn programming, let's take your first steps.

These are some basic programming concepts that you should know:

• Variable: a variable is a name that we assign to a value in a computer program. When we define a variable, we assign a value to a name and we allocate a space in memory to store that value. The value of a variable can be updated during the program.
• Constant: a constant is similar to a variable. It stores a value but it cannot be modified. Once you assign a value to a constant, you cannot change it during the entire program.
• Conditional: a conditional is a programming structure that lets developers choose what the computer should do based on a condition. If the condition is True, something will happen but if the condition is False, something different can happen.
• Loop: a loop is a programming structure that let us run a code block (a sequence of instructions) multiple times. They are super helpful to avoid code repetition and to implement more complex functionality.
• Function: a function helps us to avoid code repetition and to reuse our code. It is like a code block to which we assign a name but it also has some special characteristics. We can write the name of the function to run that sequence of instructions without writing them again.

💡 Tip: Functions can communicate with main programs and main programs can communicate with functions through parameters , arguments , and return statements.

• Class: a class is used as a blueprint to define the characteristics and functionality of a type of object. Just like we have objects in our real world, we can represent objects in our programs.
• Bug: a bug is an error in the logic or implementation of a program that results in an unexpected or incorrect output.
• Debugging: debugging is the process of finding and fixing bugs in a program.
• IDE: this acronym stands for Integrated Development Environment. It is a software development environment that has the most helpful tools that you will need to write computer programs such as a file editor, an explorer, a terminal, and helpful menu options.

💡 Tip: a commonly used and free IDE is Visual Studio Code , created by Microsoft.

Awesome! Now you know some of the fundamental concepts in programming. Like you learned, each programming language has a different syntax, but they all share most of these programming structures and concepts.  

🔸 Types of Programming Languages

Programming languages can be classified based on different criteria. If you want to learn how to code, it's important for you to learn these basic classifications:

• High-level programming languages: they are designed to be understood by humans and they have to be converted into machine code before the computer can understand them. They are the programming languages that we commonly use. For example: JavaScript, Python, Java, C#, C++, and Kotlin.
• Low-level programming languages: they are more difficult to understand because they are not designed for humans. They are designed to be understood and processed efficiently by machines.

Conversion into Machine Code

• Compiled programming languages: programs written with this type of programming language are converted directly into machine code by a compiler. Examples include C, C++, Haskell, and Go.
• Interpreted programming languages: programs written with this type of programming language rely on another program called the interpreter, which is in charge of running the code line by line. Examples include Python, JavaScript, PHP, and Ruby.

💡 Tip: according to this article on freeCodeCamp's publication:

Most programming languages can have both compiled and interpreted implementations – the language itself is not necessarily compiled or interpreted. However, for simplicity’s sake, they’re typically referred to as such.

There are other types of programming languages based on different criteria, such as:

• Procedural programming languages
• Functional programming languages
• Object-oriented programming languages
• Scripting languages
• Logic programming languages

And the list of types of programming languages continues. This is very interesting because you can analyze the characteristics of a programming language to help you choose the right one for your project.

🔹 How to Contribute to Open Source Projects

Finally, you might think that coding implies sitting at a desk for many hours looking at your code without any human interaction. But let me tell you that this does not have to be true at all. You can be part of a learning community or a developer community.

Initially, when you are learning how to code, you can participate in a learning community like freeCodeCamp. This way, you will share your journey with others who are learning how to code, just like you.

Then, when you have enough skills and confidence in your knowledge, you can practice by contributing to open source projects and join developer communities.

Open source software is defined by Opensource.com as:

Software with source code that anyone can inspect, modify, and enhance.

GitHub is an online platform for hosting projects with version control. There, you can find many open source projects (like freeCodeCamp ) that you can contribute to and practice your skills.

💡 Tip: many open source projects welcome first-time contributions and contributions from all skill levels. These are great opportunities to practice your skills and to contribute to real-world projects.  

Contributing to open source projects on GitHub is great to acquire new experience working and communicating with other developers. This is another important skill for finding a job in this field.

Working on a team is a great experience. I totally recommend it once you feel comfortable enough with your skills and knowledge.

You did it! You reached the end of this article. Great work. Now you know what programming is all about. Let's see a brief summary.

🔸 In Summary

• Programming is a very powerful skill. If you learn how to code, you can make your vision come true.
• Programming has many different applications in many different fields. You can find an application for programming in basically any field you choose.
• Programming languages can be classified based on different criteria and they share basic concepts such as variables, conditionals, loops, and functions.
• Always set goals and take detailed notes. To succeed as a programmer, you need to be enthusiastic and consistent.

Thank you very much for reading my article. I hope you liked it and found it helpful. Now you know why you should learn how to code.

🔅 I invite you to follow me on Twitter ( @EstefaniaCassN ) and YouTube ( Coding with Estefania ) to find coding tutorials.

Developer, technical writer, and content creator @freeCodeCamp. I run the freeCodeCamp.org Español YouTube channel.

If you read this far, thank the author to show them you care. Say Thanks

Learn to code for free. freeCodeCamp's open source curriculum has helped more than 40,000 people get jobs as developers. Get started

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Computer Programming Basics  - Introduction to Computer Programming

Computer programming basics  -, introduction to computer programming, computer programming basics introduction to computer programming.

Computer Programming Basics: Introduction to Computer Programming

Lesson 1: introduction to computer programming, introduction to programming.

Computer programming is the process of designing and writing computer programs . As a skill set, it includes a wide variety of different tasks and techniques, but our tutorials are not intended to teach you everything. Instead, they are meant to provide  basic, practical skills  to help you understand and write computer code that reflects things you see and use in the real world. 

What you need to know

Our computer programming tutorials assume that you have no programming experience whatsoever. They do, however, require basic familiarity with the use of computers and web browsers. For example, you should be comfortable downloading and opening files, and using text editing software. If you don't feel confident in those skills, consider spending some time with these tutorials first:

• Computer Basics
• Internet Basics

As long as you are comfortable with those basics, you should be prepared to begin learning programming. 

What these tutorials will cover

These tutorials focus on one particular type of programming:  web development . When you visit websites , whether you use a laptop, a smartphone, or anything else, you're actually looking at computer  code , which a web developer likely wrote, and which your web browser is interpreting to show you what you see on the screen. 

These tutorials will show you how to begin writing three common types of code used in web development, which combined make up the average website that you see every day: HTML , CSS , and JavaScript .

Parts of a website

Imagine that every website you visit is a person. Every person is different in how they look, act, and speak, but they're generally made up of  the same basic pieces.

If you imagine a website as a person, you can think of HTML as being the skeleton. 

HTML is at the center of almost everything you see on the Internet. While it doesn't look like much on its own, it forms the building blocks on top of which all the other pieces rest. The HTML for an extremely simple website might look something like this:

And if you loaded that in your browser, you'd see this:

Try it yourself!

You can test some HTML yourself. Use this as a starting example:

Try entering that HTML in the input box below, then press the "View HTML" button. Make sure to  type it in exactly  as you see it.

You should see a button with the text you entered appear in the box above. It looks fairly plain, and it doesn't do anything yet, but you will learn about that later! 

Congratulations, you just wrote HTML!

If HTML is the skeleton, you can think of CSS as making up all the muscle, skin, and so on that make a person actually look like a person. 

CSS doesn't do anything on its own. Instead, it takes plain HTML and styles it to look different . It can make what you see in the browser bigger or smaller, reorganize the pieces on the page, add colors, and more. Some CSS for an extremely simple website might look something like this:

If you were to apply the above CSS to the same extremely simple website you saw before, it would look like this:

You can test that CSS yourself. Use this as a starting example:

Try entering that snippet of CSS in the input box below, then press the "Update CSS" button. Make sure to  type it in exactly  as you see it.

You should see words in the box to the right become italicized. If you do, then congratulations! You just wrote CSS!

If HTML and CSS have combined to make a person that looks like a person, you can think of JavaScript as being the brain. Without it, a person just sits there, but with it, they are active and alive.

JavaScript can change the HTML and CSS of a website in real time after it has loaded. It can hide things, add new things, change what things look like, and more. Any time something on a website changes while you are looking at it, there is a good chance that JavaScript is being used to do it. 

For example, imagine that you wanted the browser to create a pop-up greeting whenever somebody loaded the extremely simple website from before. One way would be to write some code that looks like this:

And when you loaded the website, you would see something like this:

You can test that JavaScript yourself. Use this code as an example:

Try entering that snippet of code in the input box below, then press the "Run Code" button. Make sure to type it in exactly as you see it.

You should see a pop-up just like in the example above, only with a different message. Congratulations, y ou just wrote JavaScript!

/en/computer-programming-basics/tools-to-start-programming/content/

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Principles of Computing (Part 1)

This course is part of Fundamentals of Computing Specialization

Taught in English

Some content may not be translated

Instructors: Scott Rixner +2 more

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Skills you'll gain

• Computer Programming
• Python Programming
• Combinatorics

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There are 5 modules in this course

This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course. We will augment those skills with both important programming practices and critical mathematical problem solving skills. These skills underlie larger scale computational problem solving and programming. The main focus of the class will be programming weekly mini-projects in Python that build upon the mathematical and programming principles that are taught in the class. To keep the class fun and engaging, many of the projects will involve working with strategy-based games.

In part 1 of this course, the programming aspect of the class will focus on coding standards and testing. The mathematical portion of the class will focus on probability, combinatorics, and counting with an eye towards practical applications of these concepts in Computer Science. Recommended Background - Students should be comfortable writing small (100+ line) programs in Python using constructs such as lists, dictionaries and classes and also have a high-school math background that includes algebra and pre-calculus.

Required Python knowledge, coding standards, and machine grading

This week, we will introduce you to the structure and standards of the Principles of Computing courses.

What's included

10 videos 9 readings 1 quiz 2 app items

10 videos • Total 104 minutes

• Principles of Computing • 13 minutes • Preview module
• Introduction • 6 minutes
• Required Python Knowledge • 12 minutes
• Coding Style and Standards • 11 minutes
• Python Modules • 7 minutes
• Machine Grading • 10 minutes
• Mini-project Video • 5 minutes
• CodeSkulptor • 11 minutes
• Saving in CodeSkulptor • 9 minutes
• Beyond CodeSkulptor (15:12) (optional video) • 15 minutes

9 readings • Total 90 minutes

• Required Python Knowledge • 10 minutes
• Guidelines for Coding Style • 10 minutes
• Importing Custom Modules in Python • 10 minutes
• Mini-project Description • 10 minutes
• 2048 • 10 minutes
• Math Expressions for Homework • 10 minutes
• Math Notes on Functions • 10 minutes
• Practice Mini-project - Solitaire Mancala • 10 minutes
• Python Development Environments • 10 minutes

1 quiz • Total 20 minutes

• Homework 1 • 20 minutes

2 app items • Total 120 minutes

• Assignment: 2048 (Merge) • 60 minutes
• Assignment Submission History • 60 minutes

Testing, plotting, and grids

This week, we will explain the importance of testing. We will also learn to solve problems with grids.

5 videos 4 readings 1 quiz 1 app item

5 videos • Total 34 minutes

• The Importance of Testing • 4 minutes • Preview module
• Testing • 4 minutes
• Plotting • 6 minutes
• Grids • 8 minutes
• Mini-project Video • 10 minutes

4 readings • Total 40 minutes

• Building Tests for Python Programs • 10 minutes
• Math Notes on Grid Representations • 10 minutes
• Practice Activity - Testing Solitaire Mancala • 10 minutes

1 quiz • Total 30 minutes

• Homework 2 • 30 minutes

1 app item • Total 60 minutes

• Assignment: 2048 (Full) • 60 minutes

Probability, randomness, and objects/references

This we will learn how to use probability and randomness to solve problems.

6 videos 6 readings 1 quiz 1 app item

6 videos • Total 56 minutes

• The Importance of Probability • 4 minutes • Preview module
• Basics of Probability • 10 minutes
• Expected Value • 13 minutes
• Monte Carlo Methods • 6 minutes
• Objects and References • 11 minutes
• Mini-project Video • 9 minutes

6 readings • Total 60 minutes

• TTTBoard Class • 10 minutes
• Math Notes on Basic Probability • 10 minutes
• Math Notes on Expected Value • 10 minutes
• Practice Mini-project - Nim (Monte Carlo) • 10 minutes
• Practice Activity - The Monty Hall Problem • 10 minutes
• Homework 3 • 30 minutes
• Assignment: Tic-Tac-Toe (Monte Carlo) • 60 minutes

Combinatorics, generators, and debugging

This week, we will learn how to use combinatorics to solve problems.

6 videos 5 readings 1 quiz 1 app item

6 videos • Total 68 minutes

• The Importance of Combinatorics • 4 minutes • Preview module
• Enumeration • 10 minutes
• Permutations and Combinations • 13 minutes
• Combinatorics and Password Breaking • 15 minutes
• Debugging • 18 minutes

5 readings • Total 50 minutes

• Math Notes on Enumeration • 10 minutes
• Math Notes on Permutations and Combinations • 10 minutes
• Practice Activity - Analyzing a Simple Dice Game • 10 minutes
• Practice Activity - Counting Game States • 10 minutes
• Homework 4 • 30 minutes
• Assignment: Yahtzee • 60 minutes

Counting, growth of functions, higher-order functions

This week, we will explain the importance of counting in solving complex problems.

6 videos 7 readings 1 quiz 1 app item

6 videos • Total 61 minutes

• The Importance of Counting • 4 minutes • Preview module
• Counting and Sums • 14 minutes
• Functions: Finding the Max • 9 minutes
• Higher-order Functions • 11 minutes
• Plotting Statement Counts • 13 minutes
• Mini-project Video • 7 minutes

7 readings • Total 70 minutes

• BuildInfo Class • 10 minutes
• Math Notes on Arithmetic Sums • 10 minutes
• Math Notes on Logarithms and Exponentials • 10 minutes
• Math Notes on Growth Rates of Functions • 10 minutes
• Practice Activity - Modeling the Growth of Functions • 10 minutes
• Practice Activity - The Case of the Greedy Boss • 10 minutes
• Homework 5 • 30 minutes
• Assignment: Cookie Clicker • 60 minutes

Rice University is consistently ranked among the top 20 universities in the U.S. and the top 100 in the world. Rice has highly respected schools of Architecture, Business, Continuing Studies, Engineering, Humanities, Music, Natural Sciences and Social Sciences and is home to the Baker Institute for Public Policy.

Recommended if you're interested in Software Development

Rice University

Principles of Computing (Part 2)

Fundamentals of Computing

Specialization

Algorithmic Thinking (Part 2)

An Introduction to Interactive Programming in Python (Part 1)

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Reviewed on Apr 29, 2017

Really great course, understanding deeper some principles of computing. Great staff too.

Reviewed on Feb 19, 2018

Another wonderful class in this series. Great, engaging instructors and interesting projects.

Reviewed on May 28, 2016

Awesome course! Recommend to newcomers and intermediate alike. The instructors are great and the content is challenging.

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• Programming Language Principles and Paradigms

Programming Language Principles and Paradigms 

PDF version of this text.

This document was built on Jan 27, 2024.

Foundations

• Introduction
• Basic Data Structures
• Compound Statements
• Function Definitions
• Class Definitions
• Executing a Module
• Python Reference Semantics
• Lexical Structure
• Entities, Objects, and Variables
• L-Values and R-Values
• Expressions
• Name Lookup
• Nested Inline Blocks
• Scope in Functions
• Static Scope
• Dynamic Scope
• Point of Declaration or Definition
• Implementation Strategies
• Short Circuiting
• Explicit Sequences
• Compound Assignment
• Statement Sequences
• Unstructured Transfer of Control
• Conditionals
• Loop Termination
• Static Storage
• Automatic Storage
• Thread-Local Storage
• Dynamic Storage
• Value and Reference Semantics
• RAII and Scope-Based Resource Management
• Reference Counting
• Tracing Collectors
• Regular Expressions
• Context-Free Grammars
• Vexing Parse

Functional Programming

• Definitions
• Compound Values
• Symbolic Data
• Keyword Arguments
• Default Arguments
• Variadic Functions
• Parameter Passing
• Evaluation of Function Calls
• Activation Records
• Tail Recursion
• Function Objects
• Function Pointers
• Binding Policy
• Composition
• Partial Application and Currying
• Subroutines
• Signaling Errors
• Call and Return
• Non-Terminating Computation
• Normal-Order Evaluation
• Church Numerals
• Equivalent Models
• States and Transitions
• Arithmetic Expressions
• Order of Evaluation
• Boolean Expressions
• Operational Semantics for Lambda Calculus
• Subtyping and Arithmetic Operators
• The Top Type
• Subtyping and Functions
• Full Typing Rules

Data Abstraction

• Pairs and Lists
• Message Passing
• Dictionaries
• Dispatch Dictionaries
• Access Control
• Kinds of Methods
• Nested and Local Classes
• Types of Inheritance
• Class Hierarchies
• Covariance and Contravariance
• Accessing Hidden or Overridden Members
• Full Lookup and Dispatch Process
• Dictionary-Based Implementation
• Record-Based Implementation
• Type Equivalence
• Type Compatibility
• Type Inference
• Control-Flow Analysis
• Dynamic Typing
• Implicit Parametric Polymorphism
• Non-Type Parameters
• Constraints
• Implementation
• Java Generics
• Curiously Recurring Template Pattern
• Duck Typing
• Translation Units
• Modules, Packages, and Namespaces
• Information Hiding
• Initialization

Declarative Programming

• Side Effects
• Search Order and Backtracking
• The Cut Operator
• Pattern Matching

Metaprogramming

• Scheme Macros
• Stringification and Concatenation
• The Macro Namespace
• Code Generation
• Numerical Computations
• Templates and Function Overloading
• Ensuring a Substitution Failure
• Variadic Templates
• Nested Iteration

Concurrent Programming

• Multiprocessing
• The Problem with Shared State
• When No Synchronization is Necessary
• Synchronized Data Structures
• Web Crawler
• Particle Simulator
• Under-synchronization
• Over-synchronization
• Limiting the Number of Tasks
• Launch Policy

This text is based on many resources, including the classic textbook Structure and Interpretation of Computer Programs ( SICP ) by Abelson and Sussman, its Python adaptation Composing Programs by DeNero et al (available here ), and Wikipedia . These resources are all licensed for adaptation and reuse under Creative Commons.

This text was originally written for EECS 490 , the Programming Languages course at the University of Michigan, by Amir Kamil in Fall 2016. This is version 0.4 of the text.

This text is licensed under the Creative Commons Attribution-ShareAlike 4.0 International license .

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Fundamentals of Programming and Problem Solving

The mass production of computers and constant reduction in their cost has given more people access to computer technology in their homes, schools and places of work. The prevalence of computer communication hardware in developed and developing societies have given far more people access to powerful computers, in the form of desktops, laptops, handhelds, and notebooks, than was the case a decade ago. Yet, the myth surrounding the complexity of the matter of programming has kept many brilliant Caribbean scholars from pursuing programming as a business. Hence,  Caribbean nationals  remain more interested in being end-users rather than developers of computer programs.

This course seeks to change the skills set of the Caribbean Associate degree graduate by providing all ICT majors with the building blocks of problem solving and programming in C++.    It provides the right instructional conditions to develop, in students, programming skills that will enable them to create original computer programs that are solutions to problems that are unique to us in the Caribbean.

The course content challenges students to use their natural talents and creative powers to apply more imagination to the problems that exist among Caribbean societies. Thus, we hope that knowledge that is gained from this course will not only stimulate the student’s interest in pursuing a career in programming, but provide adequate foundational skills that enable those who choose to do additional programming courses to master them, and those who choose to pursue program development as a career to be exceptional creative programmers.

COURSE DESCRIPTION

This course introduces the fundamentals of computer programming and problem solving. It provides basic instructions on the process of problem solving, and deep exploration of fundamental computer-related problem solving techniques such as flowcharting, pseudo code and algorithms. It introduces students to the syntax of the  C++ programming language , and provides them with opportunities to use this language to generate solutions to real organisational and societal problems.

LEARNING OUTCOMES

On completion of this course students should be able to:

• Describe the basic control structures in C++
• Apply the principles of flowcharting to the software develop cycle.
• Create pseudo codes for real life problems and use to develop algorithms.
• Use abstraction to create Computer Software in an efficient manner.
• Analyze the features of one high level language to determine its constructs and program structure.
• Describe data types and structures for computer representation.
• Evaluate the functions and subroutines that are embedded in the C++ programming a language
• Write a simple program in C++ and use it to make decisions.
• Explain Event Driven Programming and Object Oriented Programming methods.

TEACHING AND LEARNING METHODS

To facilitate fulfilment of the requirements of this course lesson will utilise the following methods:

• Instructor Presentations
• Group and Individual Projects
• Demonstrations
• Peer-Tutoring

ASSESSMENT PROCEDURES

• Programming Assignment [20 marks]
• Programming Project [40 mark]
• Examination (40%)

ASSESSMENT SUMMARY

Nb : Dates are subjected to be changed.

TEXTBOOKS AND REFERENCES

• Zak, D.  An introduction to programming with C++.   Custom eight (8) edition, Course Technology.

READING LIST

• Farrell , J. (2014).  Programming Logic and Design, Introductory. Eight edition.
• Zak, D. (2012).  An introduction to programming with C++.  Custom seventh (7) edition, Course Technology.
• Zak, D. (2010). An Introduction to Programming with C++. Sixth (6) edition.

Course Outline 

• Revised_Fundamentals_of_Programming_and_Problem_Solving_IFTH1006_Sept_Dec_2023

Ratings and Reviews

This course was like no other, absolutely amazing!

This course is like no other you will find anywhere!

Information was easy to process.

I loved the information and doing the programming and codes.

This Course was manageable and flexible

I really enjoyed this course. It was very intriguing.

I adored both the material and the layout! Excellent work!

Provides all the necessary knowledge, and then some!

This was a great course. It allowed me to understand C++.

This course was very intriguing and easy to understanding , Inproving my knowlegde on C++

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Introduction of Programming Paradigms

• Introduction to Visual Programming Language
• Introduction to Scripting Languages
• Basic Programming Problems
• Object Oriented Programming | HCI
• Best Practices of Object Oriented Programming (OOP)
• R - Object Oriented Programming
• Functional Programming Paradigm
• Introduction to Programming Languages
• Go Programming Language (Introduction)
• Introduction of Object Oriented Programming
• Introduction to C++ Programming Language
• Programming Paradigms in Python
• Introduction to Processing | Java
• Object Oriented Programming in C++
• The Evolution of Programming Languages
• Object Oriented Programming (OOPs) in Perl
• Introduction to Perl
• Introduction to Scala
• C++ Programming Examples

Paradigm can also be termed as method to solve some problem or do some task. Programming paradigm is an approach to solve problem using some programming language or also we can say it is a method to solve a problem using tools and techniques that are available to us following some approach. There are lots for programming language that are known but all of them need to follow some strategy when they are implemented and this methodology/strategy is paradigms. Apart from varieties of programming language there are lots of paradigms to fulfill each and every demand. They are discussed below:

1. Imperative programming paradigm:  It is one of the oldest programming paradigm. It features close relation to machine architecture. It is based on Von Neumann architecture. It works by changing the program state through assignment statements. It performs step by step task by changing state. The main focus is on how to achieve the goal. The paradigm consist of several statements and after execution of all the result is stored.

Advantages:  

• Very simple to implement
• It contains loops, variables etc.

Disadvantage:   

• Complex problem cannot be solved
• Less efficient and less productive
• Parallel programming is not possible

Imperative programming is divided into three broad categories: Procedural, OOP and parallel processing. These paradigms are as follows:

• Procedural programming paradigm –   This paradigm emphasizes on procedure in terms of under lying machine model. There is no difference in between procedural and imperative approach. It has the ability to reuse the code and it was boon at that time when it was in use because of its reusability.

Then comes OOP,

• Object oriented programming –   The program is written as a collection of classes and object which are meant for communication. The smallest and basic entity is object and all kind of computation is performed on the objects only. More emphasis is on data rather procedure. It can handle almost all kind of real life problems which are today in scenario.
• Data security
• Inheritance
• Code reusability
• Flexible and abstraction is also present
• Parallel processing approach –   Parallel processing is the processing of program instructions by dividing them among multiple processors. A parallel processing system posses many numbers of processor with the objective of running a program in less time by dividing them. This approach seems to be like divide and conquer. Examples are NESL (one of the oldest one) and C/C++ also supports because of some library function.

2. Declarative programming paradigm:   It is divided as Logic, Functional, Database. In computer science the declarative programming is a style of building programs that expresses logic of computation without talking about its control flow. It often considers programs as theories of some logic.It may simplify writing parallel programs. The focus is on what needs to be done rather how it should be done basically emphasize on what code is actually doing. It just declares the result we want rather how it has be produced. This is the only difference between imperative (how to do) and declarative (what to do) programming paradigms. Getting into deeper we would see logic, functional and database.

• Logic programming paradigms –   It can be termed as abstract model of computation. It would solve logical problems like puzzles, series etc. In logic programming we have a knowledge base which we know before and along with the question and knowledge base which is given to machine, it produces result. In normal programming languages, such concept of knowledge base is not available but while using the concept of artificial intelligence, machine learning we have some models like Perception model which is using the same mechanism.  In logical programming the main emphasize is on knowledge base and the problem. The execution of the program is very much like proof of mathematical statement, e.g., Prolog
• Functional programming paradigms –   The functional programming paradigms has its roots in mathematics and it is language independent. The key principle of this paradigms is the execution of series of mathematical functions. The central model for the abstraction is the function which are meant for some specific computation and not the data structure. Data are loosely coupled to functions.The function hide their implementation. Function can be replaced with their values without changing the meaning of the program. Some of the languages like perl, javascript mostly uses this paradigm.

The next kind of approach is of Database.

• Database/Data driven programming approach –   This programming methodology is based on data and its movement. Program statements are defined by data rather than hard-coding a series of steps. A database program is the heart of a business information system and provides file creation, data entry, update, query and reporting functions. There are several programming languages that are developed mostly for database application. For example SQL. It is applied to streams of structured data, for filtering, transforming, aggregating (such as computing statistics), or calling other programs. So it has its own wide application.

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Open and Interactive Learning Resources for Algorithmic Problem Solving

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• João F. Ferreira 25 &
• Alexandra Mendes 26 , 27  

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12233))

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Algorithmic problem solving is a way of approaching and solving problems by using the advances that have been made in the principles of correct-by-construction algorithm design. The approach has been taught at first-year undergraduate level since September 2003 and, since then, a substantial amount of learning materials have been developed. However, the existing materials are distributed in a conventional and static way (e.g. as a textbook and as several documents in PDF format available online), not leveraging the capabilities provided by modern collaborative and open-source platforms.

In this paper, we propose the creation of an online, open-source repository of interactive learning materials on algorithmic problem solving. We show how the existing framework Mathigon can be used to support such a repository. By being open and hosted on a platform such as GitHub, the repository enables collaboration and anyone can create and submit new material. Furthermore, by making the material interactive, we hope to encourage engagement with and a better understanding of the materials.

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Mathigon’s website: https://mathigon.org (accessed 18 July 2019).

Wikipedia link: https://en.wikipedia.org/wiki/River_crossing_puzzle (accessed 18 July 2019).

The restatement of the problem and the subsequent two paragraphs are extracted from [ 1 ].

The implementation of the puzzle that we used was created by Victor Ribeiro ( https://github.com/victorqribeiro/bridge ).

See the repository textbooks (folder content/river-crossing ) in https://github.com/algprobsolving .

MyScript webpage: https://www.myscript.com .

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Acknowledgments

This work is partially financed by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia through the project: UID/EEA/50014/2019.

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Ferreira, J.F., Mendes, A. (2020). Open and Interactive Learning Resources for Algorithmic Problem Solving. In: Sekerinski, E., et al. Formal Methods. FM 2019 International Workshops. FM 2019. Lecture Notes in Computer Science(), vol 12233. Springer, Cham. https://doi.org/10.1007/978-3-030-54997-8_13

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Problem Solving and Programming | Unit 1 – 6 Notes

Course objectives:.

Prime objective is to give students a basic introduction to programming and problem solving with computer language Python. And to introduce students not merely to the coding of computer programs, but to computational thinking, the methodology of computer programming, and the principles of good program design including modularity and encapsulation.

• To understand problem solving, problem solving aspects, programming and to know about various program design tools.
• To learn problem solving with computers
• To learn basics, features and future of Python programming.
• To acquaint with data types, input output statements, decision making, looping and functions in Python
• To learn features of Object Oriented Programming using Python
• To acquaint with the use and benefits of files handling in Python

Examination Scheme:

In Semester : 30 Marks End Semester: 70 Marks PR: 25 Marks

Download Notes

Download question papers 🔗, unit i: problem solving, programming and python programming.

General Problem Solving Concepts- Problem solving in everyday life, types of problems, problem solving with computers, difficulties with problem solving, problem solving aspects, top down design. Problem Solving Strategies, Program Design Tools: Algorithms, Flowcharts and Pseudo-codes, implementation of algorithms. Basics of Python Programming: Features of Python, History and Future of Python, Writing and executing Python program, Literal constants, variables and identifiers, Data Types, Input operation, Comments, Reserved words, Indentation, Operators and expressions, Expressions in Python.

Unit 2: Decision Control Statements

Decision Control Statements: Decision control statements, Selection/conditional branching Statements: if, if-else, nested if, if-elif-else statements. Basic loop Structures/Iterative statements: while loop, for loop, selecting appropriate loop. Nested loops, The break, continue, pass, else statement used with loops. Other data types- Tuples, Lists and Dictionary.

Unit 3: Functions and Modules

Need for functions, Function: definition, call, variable scope and lifetime, the return statement. Defining functions, Lambda or anonymous function, documentation string, good programming practices. Introduction to modules, Introduction to packages in Python, Introduction to standard library modules.

Unit 4: Strings

Strings and Operations- concatenation, appending, multiplication and slicing. Strings are immutable, strings formatting operator, built in string methods and functions. Slice operation, ord() and chr() functions, in and not in operators, comparing strings, Iterating strings, the string module.

Unit 5: Object Oriented Programming

Programming Paradigms-monolithic, procedural, structured and object oriented, Features of Object oriented programming-classes, objects, methods and message passing, inheritance, polymorphism, containership, reusability, delegation, data abstraction and encapsulation. Classes and Objects: classes and objects, class method and self object, class variables and object variables, public and private members, class methods.

Unit 6: File Handling and Dictionaries

Files: Introduction, File path, Types of files, Opening and Closing files, Reading and Writing files. Dictionary method. Dictionaries- creating, assessing, adding and updating values. Case Study: Study design, features, and use of any recent, popular and efficient system developed using Python. (This topic is to be excluded for theory examination).

• Title: Principles of Algorithmic Problem Solving
• Author(s) Johan Sannemo
• Publisher: KTH Royal Institute of Technology (2018)
• Hardcover/Paperback: N/A
• eBook: PDF (351 pages)
• Language: English
• ISBN-10/ASIN: N/A
• ISBN-13: N/A

Algorithmic problem solving is the art of formulating efficient methods that solve problems of a mathematical nature. The purpose of this book is to contribute to the literature of algorithmic problem solving in two ways. First of all, it tries to fill in some holes in existing books. Secondly, it provides another way of learning the basics of algorithmic problem solving by helping the reader build an intuition for problem solving.

The algorithmic approach to solving problems in computer technology is an essential tool. This unique book teaches the fundamental principles of using algorithms to solve problems. It presents a readable, entertaining, and energetic book that will motivate and challenge students to open their minds to the algorithmic nature of problem solving.

• Provides a novel approach to the mathematics of problem solving focusing on the algorithmic nature of problem solving
• Uses popular and entertaining puzzles to teach you different aspects of using algorithms to solve mathematical and computing challenges
• Features a theory section that supports each of the puzzles presented throughout the book
• Assumes only an elementary understanding of mathematics
• Computer Programming
• C++ Programming
• Algorithms and Data Structures
• Functional Programming and Lambda
• Object-Oriented Analysis, Design and Programming (OOD/OOP)
• Principles of Algorithmic Problem Solving (Johan Sannemo)
• The Mirror Site (1) - PDF
• The Mirror Site (2) - PDF

Self contained with problems completely worked out in clear, readable C++11 , covers a wide swatch of advanced programming techniques, range from specialized procedures for bit manipulation, numerical analysis, subsequence problems, and random algorithms.

A comprehensive treatment focusing on the creation of efficient data structures and algorithms, using C++. This text explains how to select or design the data structure best suited to specific problems.

This book uses Python to introduce folks to programming and algorithmic thinking. It is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.

This is a textbook about computer science. It is also about Python. However, there is much more. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

This book covers Analysis and Design of Algorithms, Scientific Computing, Monte Carlo Simulations, and Parallel Algorithms. It teaches the core knowledge required by any scientist interested in numerical algorithms and computational finance.

This lecture notes uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study.

The goal of the book is to show you how you can methodically apply different techniques to your own algorithms to make them more efficient. While this book mostly highlights general techniques, some well-known algorithms are also looked at in depth.

This practical book will help you learn and review some of the most important ideas in software engineering - data structures and algorithms - in a way that's clearer, more concise, and more engaging than other materials. Useful in technical interviews too.

This book doesn't only focus on an imperative (or procedural) approach, but also includes purely functional algorithms and data structures. It teaches you how to think like a programmer - find the practical efficiency algorithms to solve your problems.

This book introduces algorithms by looking at the real-world problems that motivate them. The book teaches a range of design and analysis techniques for problems that arise in computing applications.

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. Readers will learn about computational approaches for a range of challenges.

This open access book demonstrates all the steps required to design heuristic algorithms for difficult optimization. The classic problem of the travelling salesman is used as a common thread to illustrate all the techniques discussed.

This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them.

Through investigating the everyday life of the algorithm, the book opens a conversation with existing social science research that tends to focus on the power and opacity of algorithms, via unique access to the algorithm's design, development, testing, etc.

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