Python & Machine Learning Bootcamp Series | Online
About this workshop series
This bootcamp will provide hands-on experience completing the end-to-end data science process. Students will learn to collect, explore, and clean data in a variety of formats. After cleaning and preparing data, machine learning algorithms will be applied to build a predictive model. This bootcamp is for analysts, product managers, mathematicians, business managers, or anyone else that wants to learn how to automate analysis and build predictive models in Python.
This is a very practical and hands-on workshop that has lots of class exercises. You'll build your own library of Python scripts that can be reused after your done with the bootcamp. Students will have the skills to automate data collection/cleaning processes and implement machine learning algorithms.
Takeaways
- Collect data from a variety of sources (e.g., CSV files, Excel and SQL databases) using the Pandas package
- Explore and clean/munge the data to prepare it for analysis
- Test the K Nearest Neighbors and Random Forest classification algorithms using the Scikit-Learn package
- Implement predictive model
Prereqs & Preparation
Students should have completed the Introduction to Python Bootcamp or have equivalent skills, which include the following:
- If Statements
- For Loops
- Function Definitions
- Variables
- Creating and Indexing Lists and Dictionaries
- Importing Packages
You must bring a laptop with a text editor. Students should install Anaconda, which is a free package that includes python and a number of tools that will be used in class (http://continuum.io/downloads).
