How can you learn algorithms from books, podcasts, and blogs?

Selecting the right book is not always easy and some of them are not suitable for starters. It depends on the type of algorithm or language you want to learn but online resources or official help pages are also very useful.

Books are great way to understand algorithms. Supported by rigorous practice on computer one can learn algorithms from books. There is one thing missing some books though, that is " What you could be doing wrong " The books usually have the right ways of implementing an algorithm but miss the symptoms of an incorrect implementation or common/ beginner mistakes.

Books are helpful in understanding the theory, however in order to truly grasp the concept reading reliable blogs and videos are a game changer. Creating a mental map of concepts and algorithms using these online resources will help build a strong foundation which is very critical to solve any algorithmic problem.

Asking what books to read to learn the thing - isn't doing the thing. Reading about how to do a thing - isn't doing the thing. Scheduling time to do the thing - isn't doing the thing Preparing to do the thing - isn't doing the thing. Telling people you're going to do the thing - isn't doing the thing Hating obstacles about doing the thing - isn't doing the thing. Reading this answer - isn't doing the thing. The only thing that's doing the thing is DOING the thing! - Chris Williamson So you have your answer. You will figure out the rest once you actually are doing the thing - go out there, take a problem on some platform, and start writing code.

When I was first starting out as a software engineer, I knew that I needed to learn algorithms. However, I was intimidated by the idea of learning algorithms. They seemed so complex and theoretical. At the end I ended up choosing the book Grokking Algorithms by Aditya Bhargava. This book was clear, concise, and accessible. It explained algorithms using illustrations, analogies, and real-world examples. I also liked that the book included exercises and challenges to test my understanding. I learned a lot from Grokking Algorithms. It helped me to understand the basics of algorithms and how to apply them to solve problems. I would recommend this book to anyone who is looking to learn algorithms.

The journey of learning DSA is all about building the mind's muscle to problem solve. Even though actually practicing problems has got no substitute but listening to podcasts can become a great supplement to consistent practice. Listening to podcasts ( e.g. while walking ) can allow your brain to practice visualisation and once you're able to visualise the flow of data in your mind, no problem is out of your reach. Listening to podcasts may even help you to capture certain keywords which you can later search on Google or ask ChatGPT about in order to build a solid understanding.

With professional insights and up-to-date information on the newest trends, podcasts are a handy and educational resource for algorithm learning on the go. Expand your knowledge and widen your listening experience by checking out podcasts that cover advanced subjects, real-world applications, and core principles. To gain a deeper understanding of the subject, look for interactive formats such as industry professional interviews or problem-solving sessions, and make use of the associated resources such as reading recommendations and show notes. To make podcasts a useful, continuous source of information in your life, you must be consistent in incorporating them into your schedule.

Blogs are an excellent tool for learning algorithms since they include real-world examples, instructions, and community interaction. Look beyond popular blogs to specialized platforms for in-depth analysis of particular algorithmic fields. Engage in active participation in conversations to improve networking and collaboration among the learning community. To gain practical experience solving problems, look for blogs that offer algorithmic challenges. Additionally, keep up with the most recent posts to be informed on how algorithms are changing. Think about launching a personal blog to track your educational path and encourage introspection and community involvement.

LeetCode and Interview Cake (which would be categorized under the blog section I think) also have good practice items and associated readings.

Another important aspect to take into account is that in the midst of the AI revolution today, you have the ability to inquire of GPT, Brad, or any other AI available, for book recommendations tailored to your needs, or suggested podcasts. But that's not all; you can seek their assistance for any queries you may have. If you're struggling to grasp a concept, you can delve deeper with the help of AI to ensure your understanding. If you wish to explore a topic further, simply turn to AI. AI tools offer tremendous potential, especially in the realm of learning—make the most of them!

Practice, practice and practice. Dealing with data structures and algorithms is a very tough path. You can be in a senior position and be tackled by a problem of this domain easily. Never stop learning. Algorithms are a way of thinking.

In my opinion there is just one proven way to learn and understand complex algorithms and it's actually implementing them. Just choose any programming language and try to get it running. In case of advanced algorithms patience is very helpful since not all the details will be clear from the beginning. In case you're stuck it's worth looking at somebody's else implementation to fill some blanks. These days perhaps useful approach might be usage of LLMs like GPT to do that.

My favorite resource on algorithms is AlgoExpert. It gives you different problems and allows you to test unlimited solutions and then also you get a video explanation, which is my favorite part. I tend to go back to it t refresh my knowledge practically and theoretically at the same time. And no I’m not paid, I just like it!

ChatGpt is excellent assistant for you to learn coding. You can define any interesting small and independent tasks and learn from its result.