Websites:​​

1. Towards Data Science: Sharing concepts and ideas (and code some times, super useful, thank you guys!) for data science, machine learning and programming related concepts.

2. Medium: Ideas and articles for a wide array of topics! Just choose your preferred hashtags and enjoy.

3. LeetCode: An absolute must when preparing for coding interviews. Tons of problems, alongside with solutions and a forum for discussion. I suggest the premium feature if you find the company you are interviewing for in the company tags available.

4. HackerRank: Similar to the above, a coding interview preparation website. I recommend the so-called "Interview Preparation Kit" they have: concise and straightforward.

5. Kaggle: A platform for data analytics competitions, offering prizes for the top performers! They also have a great collection of publicly available datasets.

6. DataCamp: Offering a wide range of courses (100+) in the areas of Data Science and Machine Learning. I took the "Data Scientist with Python" Track they offer and I was very satisfied. They have really good instructors and I feel they constantly growing.

7. Coursera: A classic and pioneer in the field of online courses. A ton of options from all disciplines. "Machine Learning" by Andrew Ng was my first gentle introduction to the world of ML. Totally worth the time!

8. Udemy: Similar to coursera, with less options for now but a bit more fast-paced.

9. Machine Learning Mastery: One of my favorites. WORKING CODE!

10. AI Claire: Designed to help newbies in Machine Learning and AI.

11. Data Science Central: Quoting the admins: "The online resource for Big Data practitioners".

12. Deep Learning for Self-Driving Cars: A website containing info and lectures for a class taught by Lex Fridman at MIT. Despite its name which seems a bit project-specific, I feel they cover a very wide range of topics such as Deep RL, Perception and GANs. They also have some very prestigious invited speakers and a great resources page as well.

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Books:​​

1. Reinforcement Learning: An Introduction: A wonderful book written by Sutton & Barto.

2. Deep Learning: A deep learning textbook written by Goodfellow (GANfather), Bengio & Courville.

3. Cracking the Coding Interview: The king of all prep materials in technical interviews.

4. The Hundred-Page Machine Learning Book: A quick and very explanatory introduction to ML topics.

5. Python Data Science Handbook: A handy guide to Data Science, specifically tailored for Python users.

6. The Elements of Statistical Learning: A broad coverage of Data Mining topics, useful for everyone.

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Podcasts:​​

1. AI Podcast: An amazing podcast by Lex Fridman, featuring special (Elon Musk-kind of special) guests and talks. It is somewhere between a technical and a philosophical podcast. Closer to the latter one.

2. DataFramed: Presented by Hugo Bowne-Anderson and trying to explain what exactly is Data Science. Extremely interesting invited speakers as well.

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Cheat Sheets:​

1. Big O: Exactly what it says! :-)

2. Algorithms: My own Python cheat sheet for algos and data structures. Most of the code is from LeetCode.

3. Technical Interview: A useful cheat sheet I found on GitHub.

4. Python Basics: A 26-page cheat sheet of many basic python stuff.

5. Pandas: Offered by DataCamp.

6. Keras: Offered by DataCamp.

7. TensorFlow: More a guide than a cheat sheet, offered by Bharath Ramsundar.

8. NumPy: Offered by DataCamp.

9. SQL: A handy SQL cheat sheet offered by SQL Tutorial.

10. ML Design: A guide for ML design interviews. It contains commonly asked Q&A.