Here's how you can find online resources to continue your education in Algorithms.

In my opinion, whether basic or advanced, online courses should be paid and from reputable institutions. Such courses are of high quality, markedly different from free courses, and they significantly accelerate your knowledge of algorithms.

Online course + e-books are both very helpful Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Algorithms by Robert Sedgewick and Kevin Wayne. The Algorithm Design Manual by Steven S. Skiena. Coursera has an algorithms specialisation course while Udacity has a DSA nano degree if you’re looking for a more structured learning path.

Here are some of the top platforms and resources you can use: 1)Coursera 2)edX 3)LeetCode 4)HackerRank 5)Online books 6)GeeksforGeeks 7)Youtube Channels

To find online resources for learning algorithms: 1. Online Courses and MOOCs: Platforms like Coursera, edX, Udacity, and Khan Academy. 2. Educational Platforms: Sites such as Udemy and Pluralsight. 3. YouTube Channels: MIT OpenCourseWare, freeCodeCamp, and CS50 by Harvard. 4. Textbooks and E-books: "Introduction to Algorithms" by Cormen et al., and "Algorithms" by Sedgewick and Wayne. 5. Online Articles and Blogs: GeeksforGeeks, Hackerearth, and CodeSignal. 6. Coding Practice Platforms: LeetCode, HackerRank, and Codeforces. 7. Forums and Communities: Stack Overflow and Reddit (e.g., r/algorithms, r/learnprogramming).

Online courses are helpful to kickstart your journey. Nowadays quality content is available in YouTube so for starting you can refer good coding channels to have a depth in your basic concepts

Academic journals are a joke. You submit a paper, most referees don't read it. A paper is accepted and published only if the editors and referees know you, consider you to be a member of the club, and you haven't done anything to piss them off recently. That's the truth about "academic journals". Results are constantly recycled because too much has been published and almost no one can keep up with it all.

Here are some academic journals for studying algorithms: Journal of Algorithms Journal of Algorithms and Computational Technology Numerical Algorithms Algorithmica MDPI Algorithms International Journal of Experimental Algorithms

For in-depth learning, academic journals can be helpful, but using online courses, coding platforms, and video tutorials is often more practical. These resources provide hands-on practice and up-to-date knowledge in a more accessible format.

Good coding Platforms are most important for learning coding and applying algorithms those you have learnt. There are several platforms: For DSA practice: Leetcode GFG Interviewbit For Competitive Programming: Codeforces Code Chef Atcoder etc…… Comment down your favourite platform

Interactive coding platforms, like LeetCode, HackerRank, and Codewars, offer hands-on practice, feedback, and community support, making them an excellent way to reinforce learning, improve problem-solving skills, and prepare for technical interviews in software development and data science careers.

Coding platforms are great for practicing algorithms. They offer many challenges to solve with code and have communities for feedback and solution sharing. This hands-on learning strengthens your skills and helps prepare for technical interviews in software development or data science.

Coding platforms are a great source to learn about algorithms and data structures for various programming languages. It gives you the tasks based on the basis of difficulty level which helps to build the knowledge gradually.

Interactive coding platforms are excellent for mastering algorithms. They offer challenges that enhance understanding, improve problem-solving skills, and prepare you for technical interviews. So, based on my experience (your preferences may vary): - HackerRank: Great for beginners to develop problem-solving skills. - CodeChef and Codeforces: Ideal for competitive programming and tackling complex challenges. - GeeksforGeeks: Comprehensive resources for algorithms and data structures, perfect for interview prep. - LeetCode: Excellent for practicing diverse data structures and algorithms for interviews. - InterviewBit: Similar to LeetCode but with more refined test cases, optimizing your algorithms for interviews. Happy Coding :)

The benefit of video tutorials is the ability to see algorithms in action? Nonsense. Here's something better. Get the code, compile it in your favorite language, run it and test it. There is literally nothing more effective than that when it comes to your own understanding. Who says that an expert will ask all the questions that you want answered? I know I don't.

While video tutorials are helpful, interactive coding platforms can be even better. They allow you to apply what you've learned by solving real problems, offering immediate feedback and community support. This hands-on experience is crucial for mastering algorithms and developing strong problem-solving skills.

Video tutorials are a great resource for visual and auditory learners, offering a unique learning experience. Platforms like YouTube, Coursera, and edX host tutorials on various algorithm topics, ranging from short explanations to full-length lectures. The benefits include: - Visualizing algorithms in action - Expert commentary and explanations - Enhanced understanding and retention These tutorials are an excellent supplement to traditional learning methods, making complex concepts more accessible and engaging.

I've found that diving into video tutorials on platforms like YouTube, Udemy, and Coursera really sharpens my coding skills. They break down algorithms in a way that's easy to follow and apply. Plus, the variety of content means I can always find something new to learn. It's a great way to stay current and continuously improve. Give it a shot; it's been a game-changer for me!

Tutorial videos have been incredibly helpful throughout my academic journey. Sometimes, the information or hacks you need aren't readily available in books, but platforms like YouTube and others offer solutions from experts that are easily accessible. These videos not only provide practical solutions but also inspire you to share your own knowledge and contribute to the learning community.

Advice on "learning strategies"? What has happened to the planet, honestly? The way you learn is by asking every question you can think of and finding the answer to those questions by any means necessary. That's not a strategy, it's common sense.

Discussion forums are invaluable for algorithm learning. They enable you to seek help, share insights, and connect with like-minded individuals. These communities offer diverse viewpoints and solutions, which can deepen your understanding. Moreover, actively participating by helping others not only reinforces your knowledge but also builds a supportive learning network.

Discussion forums provide a platform to ask questions, share knowledge, and connect with others interested in algorithms. Whether you're stuck on a particular problem or looking for advice on learning strategies, these communities can offer support and guidance. Engaging with peers can also expose you to different perspectives and solutions, enriching your learning experience. Remember to contribute as well; helping others can solidify your own understanding. Recommended Forums: Stack Overflow Reddit (e.g., r/algorithms, r/learnprogramming)

I've discovered that discussion forums are a treasure trove for anyone passionate about algorithms. They're a place where I can pose questions, exchange insights, and interact with fellow enthusiasts. Whenever I hit a roadblock or need insights on learning tactics, the community is there to lend a hand. It's fascinating to see the myriad of approaches to a single problem, and it definitely broadens my horizon. Plus, I make it a point to pitch in too. Sharing my two cents not only aids others but also cements my own grasp of concepts. It's a win-win!

Just learning DSA and solving DSA problems are not enough these days. So doing some cool and unique open source projects will add more value to your resume. Always start with a basic new language or topic and try to build something on your own. It will also boost your confidence

Engaging with open source projects has been a transformative experience for my coding skills. It's one thing to learn code in isolation, but applying it to real-world applications is a whole different ball game. It's taught me not just about algorithms, but also about system design and the nuances of software engineering. Working alongside experienced developers has accelerated my learning curve, and contributing to projects that resonate with me has been incredibly fulfilling. It's a rich learning environment that I'd recommend to any coder looking to grow.

Contributing to open source projects provides an invaluable platform for enhancing algorithmic prowess. By tackling real-world problems, you not only refine coding skills but also deepen understanding of algorithmic applications in diverse contexts.

Critical thinking is essential in algorithm design. One effective approach is to create problems based on real-life challenges you've encountered and work towards finding optimal solutions for them. This practice not only enhances your problem-solving skills but also deepens your understanding of algorithmic principles.

The entire trend toward online learning is an affront to humanity. It literally is the first step toward making humans half machine. It's also a good vehicle for managers that contribute nothing to pretend they are doing something, and lazy educators that want to collect a paycheck for simply posting videos.

I am a software inventor, I create algorithms that don’t exist yet that GPT chat cannot do. Teaching people to think, is harder than teaching people to memorize. The bestway to learn about algorithms is to create some on your own. The reality is that creativity is needed if you have a unique problem to solve.

Books. And because of the semantic shift, let me be specific: actual published printed books, in libraries. Not everything is online, and books have gone through a stricter quality filter. Very often, online material, including millions of unpublished pre-prints, contains wrong information.

I've found that using course web pages and lecture notes from top universities has been incredibly valuable for learning. These resources often include high-quality examples, foundation for the proofs, and challenging questions that offer valuable insights. Practicing on online judges afterward reinforces these concepts effectively.