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10+ Data Science materials for self-study

Where can you study theory and develop your Data Science skills? Resource Development Team Leader Hanna Petrashka and her colleagues compiled a list of useful materials that will help you master the principles and tools of Data Science and understand how to become a data scientist without a degree.

Resource Development Team Leader Hanna Petrashka



Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFLow 2, by Sebastian Raschka and Vahid Mirjalili


This book is immensely popular with novice developers since it explains complex concepts in plain language, and there is an excellent balance between theory and practice. It is a great starting point for those who are beginning their journey into Machine Learning and Data Science and want to learn the basic concepts.

Deep Learning for Computer Vision with Python, by Dr. Adrian Rosebrock


This book touches on the basics of teaching Computer Vision as well as the construction of Neural Networks, Deep Learning, and even Convolutional Neural Networks. It is aimed at novice professionals who are at the beginning of data scientist career path but there are two more volumes for those who want to continue their study and development in the area.

Pattern Recognition and Machine Learning (Information Science and Statistics), by Christopher M. Bishop


Despite the seeming complexity of this area of study, this book on the theory of Pattern Recognition reassures future readers — to master it, you do not need deep knowledge in ML or PR, it is enough to know linear algebra, multivariate analysis, and a pinch of probability theory. The book is an ideal guide for students of technical specialties, or those who are simply fans of mathematics.

Deep Learning, by Ian Goodfellow, Yoshua Bengio, and Aaron Courville


This is one of the most recent and profound books on Deep Learning. It is written in plain language and is therefore suitable for readers of all skill levels. It is considered the reference book of any Data Science specialist due to its structured presentation of information and a decent mathematics background. An enthusiastic review by Elon Musk calls it “the only comprehensive book on the subject” in the DL field.


Towards Data Science

This board on the Medium platform is dedicated to all aspects of Data Science with consistently helpful, hands-on material for developers. We strongly recommend that you keep an eye on the release of new articles, and feel free to get in touch for reliable information from DS specialists.



This platform from Google functions as a communication platform and a competition arena for developers. You can take part in public competitions offered by large companies to gain experience in working on practical tasks — from analyzing user behavior (Anti-fraud systems) to recognizing deep fakes.


Another product from Google, this is an environment for running Python code directly in the browser. It is a free and convenient cloud solution promoted as a product for researchers in the artificial intelligence field.

ODS competitions

ODS is an open platform for DS specialists from around the world. There are free courses on Machine Learning, Neural Learning, and Deep Learning that are considered basic (and the best) for beginners, as well as classic competitions focusing on speech recognition, photo orientation, real-time tracking, etc.




Our thanks to our partner site training.epam.com.

You can learn more about the skills required for a data scientist or read about career change to data science.

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