NOTE TO STUDENTS: This is not a statistical theory, methods, or computing course. The course expects all students to have mastered standard graduate-level mathematical statistics, probability, and statistical methodology. The course also expects all students to know how to use the R software, Github, Python, iPython/Jupyter Notebook, Unix, and other relevant computer science skills for data science. In particular, the course will not provide any assistant in debugging R/Python or iPython/Jupyter code.
- Please use google first, DO NOT let me send the following link to you !!!!lmgtfy
- Use stackoverflow wisely. How to search in stackoverflow and Help Center
- Use Python library: Scipy: Numpy, Pandas, Matplotlib, IPython, scikit-learn
- How to ask a good question
- Use Anaconda if you don’t want to read anything.
Some Books and Websites you may interested:
- Computing Tools for Data Analytics
- Machine Learning in Action python
- Learn Python the Hard Way
- Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
- Some books recommendation from quantstart
- Websites to learn Python
The best way to learn a language is to use it.