Community Tips

Where to Practice Programming for Free: Links and Tips

Learning to code is a challenging task, especially if you’re a beginner. But if you are properly equipped, everything is possible. This article contains useful links and recommendations to achieve your coding goals faster and without spending any money.

The Reasons to Code

Actually, there are many reasons why a person may want to become a programmer. Some want a more fulfilling job, while others dream about social status and a big salary. Any motivation is reasonable: a developer’s job is indeed prestigious and well-compensated. Also, it’s highly in demand.

You may have heard about layoffs that happened last year. Many tech companies had to take this step because of the market situation. Nevertheless, it’s much easier for a developer to find a new job than other specialists. Here are some numbers: according to the U.S. Bureau of Labor Statistics, employment of software developers, quality assurance analysts, and testers is projected to grow 25% from 2022 to 2032. This growth rate is much bigger than the average for all occupations. It means about 153,900 new openings each year over the decade.

This trend is worldwide. According to Statista, we can expect the number of software developers to reach 28.7 million in 2024. Compared to 2020, it means an increase of 3.2 million. The biggest growth is going to happen in China. In general, the Asia-Pacific region’s growth rate will reach 17%, North America’s – 15%, and Latin America’s – 14%.

Therefore, developers may feel more secure than other professionals, especially if they keep their skills and theoretical knowledge up to date and embrace a lifelong learning approach.

Where and How to Learn?

Coding is much like riding a bicycle. It’s a practical skill, and you need to start solving tasks as soon as possible to get better. Sure, you can watch videos and read books or articles, too, but the magic won’t happen until you begin writing code. 

There are many ways to learn, but according to recent research, online courses are the most popular. Almost 50% of developers prefer an online course.

top 5 ways developers learn to code

You should be aware that sometimes practice may seem boring. After all, you need to learn syntax, so you’ll solve many similar tasks. But don’t be discouraged: we’ve created a list of websites that can make studying exciting!


If you’re just starting in programming or already have some experience, CodeGym is your go-to place. This platform offers a bunch of tasks perfect for getting some coding practice for free. The topics cover everything from basic commands to conditions, loops, arrays, methods, strings, and much, much more. Plus, you can get instant feedback on your solutions (automatic verification). On the CodeGym’s platform, you will find links to theory connected to the tasks you’re solving. So, you’re acquiring both theoretical and practical knowledge simultaneously.


Cooking up some coding skills? CodeChef has four free topics for you to explore: input, output and arithmetic; conditionals; loops with conditionals; and debugging. The tasks are quite creative, for example, the website suggests you solve the Chef and Instant Noodles task. Imagine inventing 1-minute Instant Noodles. How many customers can you serve in Y minutes if the restaurant has X stoves and every customer orders just one portion of noodles? And fear not, solutions and discussions are right there for you to dive into.


This platform provides coding challenges for various programming languages at different difficulty levels. From summing two numbers to converting minutes into seconds, there are tasks for everyone’s level of expertise. Each task comes with explanations, examples, and notes, making it beginner-friendly. This website aims to provide users with small, solvable challenges so they can incorporate coding practice into their usual schedule.


Codingame brings coding challenges and a gaming experience together. It supports multiple programming languages, so you can pick your favorite. You can practice writing solo games or multiplayer ones. Each turn brings new inputs for your program to tackle – it’s coding meets gaming!


CodeHS offers a variety of tasks in different languages, and users get points for solving them. Want to calculate the area of a triangle? That’s worth two points! The platform has several levels of difficulty, and its big advantage is the opportunity to code directly in the browser. It makes learning convenient and interesting at the same time.


If you’re looking for a challenge, this platform offers it. It has tasks ranging from easy to hard, covering algorithms, databases, and much more. You can practice your coding skills in different programming languages and showcase your solutions. Hence, you work on your problem-solving skills while studying!

How to Make the Most of Learning?

Some of the hardest things in studying programming are keeping your motivation up and sticking to the schedule. Discipline doesn’t come easy to many people, and if you’re like that, you can benefit from these recommendations:

1. Set clear learning goals. “Study programming” isn’t specific enough to keep your engine running. “Find a job in 3 months” isn’t realistic enough, so if you go for it, you’ll be inevitably disappointed. The best approach is to set small and achievable goals. For example, you can have a goal for every learning session (say, “learn about strings and solve three tasks”), a goal for a week, and a goal for a month.

2. Try to understand, not just memorize. Sure, becoming a programmer requires some memorizing. You must remember the basic syntax, etc. But most often, you’ll need to think creatively and analytically to solve tasks. So, start training early. Analyze problems, build algorithms to solve them, and then write code.

3. Practice constantly and regularly. Yes, it’s hard, but this is the only way to transform your efforts into results. Try finding some time (at least half an hour!) every day, and it will bring you more value than weekly 3-hour sessions. If you have ever tried to build muscles, you know it’s true. Moreover, the more regularly you study, the easier it is to beat procrastination. Why? Because your brain will remember the feeling of achievement you had just yesterday and the day before.

4. Mix it up a little. Sometimes, it’s the routine that kills motivation. If all your study sessions are the same, you’ll get tired. So, try different forms of learning: from reading to watching, from coding challenges to practicing solving simple tasks, from writing games to giving feedback to fellow learners.

5. Find like-minded people. Luckily, the internet offers many options. There are online communities like Redditt where you can find people learning the same language as you. Participate there actively, ask for help when needed, and help others when they ask. You’ll get a boost in your motivation, and maybe you will even make some friends.

6. Reflect on your goals. We all need to analyze the steps we made and rethink our goals. Do it regularly, and you’ll see an increase in your learning productivity.

At the beginning of the article, we’ve said that coding is a challenging task. But at the same time, it’s achievable and very rewarding. So, it totally makes sense to go for it!

Dmytro Vezhnin, CEO and Co-founder at, an interactive educational platform where people can learn Java programming language from scratch to Java Junior level. LinkedIn:

Community Tips

Navigating the New Era of Learning: Top Generative AI Books for Programmers

Hello, we’re Computer Science Professors Dr. Leo Porter and Dr. Daniel Zingaro. We’ve dedicated our careers to helping students succeed in programming and computer science courses. There are approaches we know are effective in teaching novices, such as learning from worked-out examples and using real-world problems that resonate with students. When we’re reading a book, we’re always thinking: will this book help people learn? Does it use what we know about learning to serve as an effective teaching aid? Can we use this with our students? Can we for once stop analyzing the book and just read for fun? (The answer to that last question is, unfortunately, ‘no,’ 😀 We can’t help it!)

With massive changes happening due to generative AI tools like ChatGPT and GitHub Copilot, you won’t be surprised that there’s a swarm of new books that use generative AI to teach programming to beginners or to enhance what programmers can do.

In this article, we wanted to cover our top four generative AI books that are being published by Manning Publications.

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Introduction to Generative AI
Introduction to Generative AI: An ethical, societal, and legal overview Numa Dhamani and Maggie Engler

We know, we know: you just want to use generative AI to supercharge your programming productivity. We want that, too! But we’re at the dawn of a programming revolution here, and we strongly encourage you to take the time to understand the ethical and legal concerns wrought by generative AI. 

What happens when generative AI models ingest objectionable speech or personal data? Why are these models apt to produce hallucinations, and why should we care? Why is it so difficult to address bias in machine learning? What is the critical role that human feedback plays in LLM training, and what are the associated costs to humans? Does generative AI’s use of copyrighted work fall under fair use?

As informed end-users of generative AI, it’s up to us to answer these questions–to understand what data we might be using, how that data was produced, and the societal and ethical impacts of these tools. This book helps us toward those answers.

We appreciate that many claims in the book are supported with references that the reader can check for additional details. We also benefited from numerous powerful examples throughout the book, such as racial bias in movie sentiment scores, a ChatGPT data breach, and a famous virtual influencer.

We’d also like to emphasize that while the focus of the book is on the responsible use of generative AI, there is also a non-mathematical overview coverage of how generative AI tools work, which we suspect will be of interest to many readers. For example, you’ll learn more about many concepts you’ve probably heard about in passing, such as foundation models, fine-tuning, emergent properties of LLMs, zero-shot and few-shot learning, and chain-of-thought prompting.

Finally, we applaud the balanced discussion of the pros and cons of synthetic media, the ways that LLMs are and will be misused, the ways that professionals are using LLMs and–of course!–the coverage of the impacts on education.

Dhamani and Engler’s Introduction to Generative AI is a must-read foundational guide not only to understand how generative AI works but also to understand its broader societal implications.

Learn AI-Assisted Python Programming
Learn AI-Assisted Python Programming: With GitHub Copilot and ChatGPT Leo Porter and Daniel Zingaro

The two of us (Daniel Zingaro and Leo Porter) wrote this book because we believe that the way new programmers learn to program has changed dramatically now that generative AI is here. We’ve both taught thousands of students to program over the years and a lot of our time needed to revolve around teaching syntax, which is the ways that words and symbols are put together to create programs that run. But generative AI handles syntax extremely well (which is a good thing, because many learners find syntax boring and frustrating). So, in writing this book, our guiding question was: what are the main skills that new programmers need to learn now?

In this book, written for absolute beginners, you’ll be writing programs that work from day one, in contrast to the before times when you would have had to learn lots of syntax first. You’ll learn how to test code that comes from the generative AI to check whether it is correct, break down large problems into smaller bits that the AI can better solve, and use a debugger to trace your code very carefully to see what it’s doing. Oh, and you’ll be learning Python along the way, too, in case you need that for your resume 🙂

Why would you buy and read a book with ‘obsolete’ in the title? What the author is getting at with this irreverent title is that generative AI is moving so quickly that everything written about it will be obsolete quickly. We may as well understand the foundations of effectively interacting with these tools, which is what this book focuses on.

The book starts by explaining the background concepts you need to know when working with generative AI tools. What’s a token? What are the differences between all of those GPT models? What the heck is temperature and Top P?

You need Python experience to read this one. This isn’t a programming book, though. It’s a “let’s see what we can do with generative AI!” book. You’ll generate fiction (not very good fiction… yet?), generate book cover images, convert slides to videos, and quickly obtain summaries of boring meetings and long PDF documents. The book tours many powerful generative AI tools that you may not have been aware of–it goes way beyond what the general public is doing with ChatGPT.

The key takeaway of the book is that the best results come from pairing your domain knowledge with the explosion of content you can create with generative AI.

AI-Powered Developer: Build great software with ChatGPT and Copilot Nathan B. Crocker

OK — so you’re already a Python developer and you want to start using LLMs to rocket your productivity. How? By reading Crocker’s new book 😀

This book shows you how to use GitHub Copilot, ChatGPT, and Amazon CodeWhisperer (and when to use each). It assumes that you already know Python, and we further suggest that familiarity with building APIs in Python would be a plus.

Through its chapters, you’ll build an Information Technology Asset Management (ITAM) system, using generative AI for each step… from designing the system to writing the code, generating data, testing and managing the deployment, and helping with security. (Yes: generative AI is useful way beyond writing code for you!)

The pro of writing the book as one comprehensive example is that you see how a complete application is built and deployed with generative AI help. The cons are that it makes it difficult to jump around the book and that if you are not motivated by the chosen example then the book itself may not be as motivating as a collection of smaller examples. We need books of both types!

For us, the material on system design is of particular interest, because in our time working with generative AI, we have done the high-level design and left the low-level code to the AI. Crocker’s book shows that experienced programmers can indeed push generative AI into the design realm as well, including proposing designs, creating class diagrams for designs, and comparing and contrasting potential designs.

Whether you want to understand generative AI at a societal level, to learn programming from scratch “the new way,” to add generative AI to your programming toolbox, or to be inspired to use generative AI to … generate (sorry!) content, we’re confident that you’ll find value in one or more of these books.

Manning Publications is a premier publisher of technical books on computer and software development topics for both experienced developers and new learners alike.

Manning prides itself on being independently owned and operated, and for paving the way for innovative initiatives, such as early access book content and protection-free PDF formats that are now industry standard.