Helpful resources for learning Data Science
Our team regularly gains new experience in the company’s projects, as well as outside: they study in various courses, read scientific articles, listen to professional podcasts, and so on. And they are happy to share this knowledge with the developer community.
Our data science team has created a list of useful resources that they use to pump up their own skills. This list is the best way to learn Data Science for developers of any level. We hope this information will be useful to you. We hope this information will be useful to you.
Course MIT Open Courseware
The course provides a wide variety of computer science, statistics, and calculus learning materials including lectures, notes, exercises, and workbooks. If you are new to statistics, an introductory course on Probability and Statistics might be a good place to start.
The podcast and YouTube channel Machine Learning Street Talk
The podcast is an outstanding resource for any data science and machine learning practitioner. It not only helps to stay up-to-date with current state-of-the-art research in the field but also digs deeper into the mechanisms of each particular technique, practical concerns of AI applications, and much more.
Community forum Jovian
Jovian is a great platform to connect to like-minded people. Mostly the audience consists of people who want to or are on the way to transitioning to the data science path. But anyone can find herself a companion to look up to. This is more than a forum, however. There are several courses (most of which are completely free), learning materials, and boot camps, and one can even host and share Jupyter notebooks.
Google AI Blog, Meta AI Blog, OpenAI Blog
Latest machine-learning news from leading AI research centers. Each blog post is a brief overview of recent ML advancements accompanied by detailed explanations, listed resources, papers, and codes.
Resource Papers with Code
A free resource for researchers and practitioners to find and follow the latest state-of-the-art machine and deep learning papers, code, results, and comparisons.
Stanza is a natural language processing library. Compared to popular NLTK and Spacy toolkits, this library stands out with sophisticated, powerful, and diverse functionality for natural language processing and analysis. If their syntaxis scares you, do not worry, Spacy provides a wrapper spacy-stanza around it which is more user-friendly.
We are excited to be able to invest in the future of technical education and technological progress by building a knowledge base among young professionals.
Enjoy getting to know our wealth of experience! Learn more about our case studies and R&D project descriptions.
