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.
Objectives
- Develop comprehensive skills in the importing/exporting, wrangling, aggregating and joining of data using Python.
- Establish a mental model of the Python programming language to enable future self-learning.
- Build awareness and basic skills in the core data science area of data visualization.
Pre-work
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):
- Visit the Anaconda download page
- Select your appropriate operating system
- Click the “Download” button for Python 3.7 - this will begin to download the Anaconda installer
- Open the installer when the download completes, and then follow the prompts. If you are prompted about installing PyCharm, elect not to do so.
- Once installed, open the Anaconda Navigator and launch a Jupyter Notebook to ensure it works.
- Follow the package installation instructions to ensure pandas and seaborn packages are installed.
Agenda
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| 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 |