Course Schedule¶
The following table provide a detailed view of the course schedule as it is currently planned. As mentioned earlier, this tentative schedule might evolve as the term advances.
Week # |
Week |
Course Topics |
Labs |
Project |
Test |
Test Concepts |
|---|---|---|---|---|---|---|
1 |
January 11 - 17 |
Introduction to Data Analytics and Community Building |
Lab 0: Installation and setup |
- |
- |
- |
2 |
January 18 - 24 |
Command line and Microsoft Excel |
Lab 1: OS file systems & Excel |
- |
- |
- |
3 |
January 25 - 31 |
Command line and Jupyter Lab |
Lab 2: Git & command line |
- |
Test 1 |
Git; OS and Excel |
4 |
February 1 - 7 |
Introduction to Python |
Lab 3: Python I |
- |
Bonus Test 1 |
- |
5 |
February 8 - 14 |
Programming in Python |
Time for Project |
Milestone 1: Topic/area/dataset |
Test 2 |
General Python |
6 |
February 15 - 21 |
Rest and Catchup (no new material) - Reading break |
N/A |
- |
Bonus Test 2 |
- |
7 |
February 22 - 28 |
Data analysis in Python |
Lab 4: Python II |
- |
- |
- |
8 |
March 1 - 7 |
Introduction to Data Visualization |
Lab 5: Git and Data Visualization |
- |
Test 3 |
Pandas and Python Functions |
9 |
March 8 - 14 |
Choosing an appropriate visualization & EDA |
Time for Project |
Milestone 2: Data Analysis |
Bonus Test 3 |
- |
10 |
March 15 - 21 |
Introduction to Tableau |
Lab 6: Tableau |
- |
Test 4 |
Data Visualizations |
11 |
March 22 - 28 |
Introduction to Databases |
Time for Project |
Milestone 3: Cleanup and addressing feedback |
Bonus Test 4 |
- |
12 |
March 29 - April 4 |
Working with Databases |
Lab 7: SQL I and Lab 8: SQL II (Tentative) |
- |
Test 5 |
Databases |
13 |
April 5 - 11 |
Introduction to R (tentative) |
- |
- |
Bonus Test 5 |
- |
14 |
April 11 - 13 |
Poster Session |
Lab 9 : Poster Session |
Milestone 4: Final Project |