5 Ways to Expand Your Knowledge in Data Science Beyond Online Courses
Dive deep into core data science concepts using these resources
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Key takeaways
- In today’s modern world of information technology, there are unlimited online resources for learning data science.
- Most of the data science resources provide superficial knowledge only.
- To expand your knowledge beyond online courses, you must put in extra effort to gain in-depth knowledge of core data science concepts.
There are unlimited online resources for learning data science. Some of these resources can be found on platforms such as YouTube, KDnuggets, Medium, or on platforms that offer massive open online courses in data science such as the following:
While it is beneficial to use these resources as a starting point for learning the basics of data science concepts, more effort is need to expand one’s knowledge beyond the fundamentals.
Data Science Textbooks
Textbooks are recommended as great teaching tools for advanced learners who are interested in diving deep beyond what is covered in online courses. For me personally, one textbook that stood out to me (I still consult this book as my main reference when working on data science projects) is the book: “Machine Learning with PyTorch and Scikit-Learn”, by Sebastian Raschka. This book provides a great introduction to data science and machine learning, with code included. The GitHub repository for this book with code for all chapters can be accessed by clicking on this link: https://github.com/rasbt/machine-learning-book
This book is one of the best data science books out there for beginners. The author explains fundamental concepts in data science and machine learning in a way that is very easy to follow. Also, the code is included, so you can actually use the code provided to practice and build your own models. I have personally found this book to be very useful in my data science journey. I would recommend this book to any data science…
