Here are some resources for learning data science if you have Python experience. If you haven't coded in any language then perhaps see Learn to Code, in Python. Or if you do code but want to get up to speed on Python, maybe try Learn Python (or search frequently). And please contact us if you have suggestions.
The University of Michigan's course on Applied Data Science with Python Specialization comes highly recommended by some microprediction participants.
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.
Contains a nice section on data science tools with a curated list of resources, covering topics such as OOP best practice, type checking, concurrency, async, coroutines, virtual environments, efficient use of numpy, speeding up pandas and so forth.
This is the Century of Statistics (just ask Jeb Bartlett). Your time has not been wasted.
You're ready for Python Module 1 which will get you on the leaderboard!
Didn't like these suggestions but something else helped? Please contact us with suggestions for how to help others get up to speed with Python.
