Tutorials

Below you will find a list of available tutorials with instructions on how to install and use the tools we will be using in class.

Available Tutorials

• 01 - VSCode and Anaconda Tutorial
• 02 - Jupyter Notebook and Markdown Tutorial
• 03 - GitHub Tutorial

PDF versions of the tutorials are also available on GitHub: https://github.com/danilofreire/datasci151/tree/main/tutorials.

Additional Resources

Further examples

• testing-ipython.ipynb: A Jupyter Notebook for showing Markdown and code cells
• testing-anaconda.py: A Python script for testing Anaconda installation

Suggested Books

• Python for Data Analysis by Wes McKinney
• Elements of Data Science by Allen Downey
• Automate the Boring Stuff with Python by Al Sweigart
• Python for Everybody by Charles Severance
• SQL for Data Scientists by Renee M. P. Teate

Online Courses

• Coursera: Python for Everybody Specialisation
• edX: Python Basics for Data Science
• Codecademy: Learn Python
• DataCamp: Introduction to SQL
• Coursera: SQL for Data Science

Documentation

• Python Documentation
• Pandas Documentation
• PostgreSQL Documentation
• SQLBolt
• Github Guides

For any questions or issues regarding these tutorials, please open a GitHub issue, submit a pull request, or create a discussion post.

Please do not forget that, in addition to the tutorials here, the course syllabus also contains a list of recommended weekly readings and additional resources.

I hope you like the tutorials and find them useful!