Legally allowable public portion of the UCSD Extension course: Data Analytics Using Python (CSE-41204).
| Lecture Number | Topic | Content Folder | Video |
|---|---|---|---|
| 1 | Introduction (powerpoint) | Session 1 | Introduction |
| 1 | Installation and Python Basics (powerpoint) | Session 1 | Jupyter Notebooks, Strings, Simple Math, and Lists |
| 2 | Tuples, Dictionaries, and Reviewing Exercises (screen sharing) | Session 2 | Tuples, Dictionaries, and Reviewing Exercises |
| 3 | Pandas Part 1: Reading and Writing Files, Filtering and Sorting Data (screen sharing) | ||
| 4 | Pandas Part 2: Handling Missing Values, Combining Dataframes, GroupBy (screen sharing) | ||
| 5 | Matplotlib (Plotting) + Logistic Regression (screen sharing) | ||
| 6 | Train Test Split + Logistic Regression + Decision Trees (screen sharing) | ||
| 7 | Metrics + Random Forests (screen sharing) | ||
| 8 | Clustering | ||
| 9 | Dimensionality Reduction: Principal Component Analysis | ||
| 9 | Topics of Interest: Things We Dont have Time to Cover |
- Installing Python/Jupyter/IPython on Windows and Mac
- Python Basics (variables, strings, simple math, conditional logic, for loops, lists, tuples, dictionaries, etc.)
- Using the Pandas library to manipulate data (filtering and sorting data, combining files, GroupBy, etc.)
- Plotting data in Python using Matplotlib and Seaborn
- Logistic Regression using Scikit-Learn
- Classification and Regression Metrics
- Decision Trees using Scikit-Learn
- Random Forests (Scikit-Learn)
- Clustering Algorithms (K-Means, Hierarchical Clustering)
- Dimensionality Reduction (Principal Component Analysis)
- Hands on programming assignments that are reviewed weekly via screen sharing videos
- The primary assignment for this class is a project of a student’s choice.
Online in Fall, Winter, Spring, and Summer.
Students will use Python 3.x/Jupyter/IPython to complete hands-on assignments (if for some reason you insist of using Python 2.x, that is fine too). All These tools are free and open-source.
None. General programming knowledge is helpful.