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Python for Data Science Bootcamp

The Python for Data Science Bootcamp is one-day training, beginning at 8am and finishing at 5pm or a little earlier. The bootcamp uses the materials from my Intro to Python for Data Science repository.

If you are looking for information on the associated course, click here.


  1. Develop comprehensive skills in the importing/exporting, wrangling, aggregating and joining of data using Python.
  2. Establish a mental model of the Python programming language to enable future self-learning.
  3. Build awareness and basic skills in the core data science area of data visualization.


I try to limit pre-work as much as possible, but having Python, Jupyter, and the relevant packages installed is an unavoidable necessity. Below are instructions to do so via Anaconda (a popular Python distribution):

  1. Visit the Anaconda download page
  2. Select your appropriate operating system
  3. Click the “Download” button for Python 3.7 - this will begin to download the Anaconda installer
  4. Open the installer when the download completes, and then follow the prompts. If you are prompted about installing PyCharm, elect not to do so.
  5. Once installed, open the Anaconda Navigator and launch a Jupyter Notebook to ensure it works.
  6. Follow the package installation instructions to ensure pandas and seaborn packages are installed.


{% comment %} Super hack! I need to style [only] this particulary table but it’s generated from a markdown file. This approach is stylistically terrible for a variety of reasons – but it works. {% endcomment %}

Time Content Materials
8:00-8:15 Introduction of Your Instructor; Overview of the Day’s Agenda
8:15-8:45 Basics of Python and Jupyter Notebook 1
8:45-9:30 Python Fundamentals Notebook 2
9:30-10:15 The Mental Model of Python Notebook 3
10:15-10:30 Break
10:30-11:00 Importing and Exporting Data Notebook 4, Notebook 11
11:00-11:45 Selecting and Filtering Data Notebook 5
11:45-1:15 Lunch
1:15-2:00 Manipulating Columns Notebook 6
2:00-3:00 Summarizing Data Notebook 8
3:00-3:15 Break
3:15-4:15 Summarizing Data by Group Notebook 9
4:15-5:00 Questions, Discussion, and Review