AI Data Science Club

Classes

Explore current classes and see how students progress from Python fundamentals to data analysis, AI literacy, and clear communication.

Current classes

Current fall classes

Two five-session learning tracks running from August through October.

Ongoing

Beginner Python

Python fundamentals in five guided sessions.

Dates
Aug. 22 & 29 · Sept. 12, 19 & 26
Time
7–8 p.m.
Level
No prior experience

Project-based Data Science

Apply Python to data-science questions in five projects.

Dates
Aug. 22 · Sept. 12 & 26 · Oct. 3 & 24
Time
8–9 p.m.
Level
Basic Python required
Students participating in an online data-science class

Course schedule

Class topics and dates

See what students will cover in each class, from opening and cleaning data to analysis and visualization. Three dates are still waiting for topic details.

12 class dates 9 announced topics 3 topics to come

  1. Introduction to Data Science

    What data science is, where it is used, and how data becomes insight.

    Topic announced

  2. Get and Look at Data

    Finding data, understanding its structure, and asking useful first questions.

    Topic announced

  3. Upload and Open Data

    Bringing datasets into the working environment and checking them safely.

    Topic announced

  4. Topic to be announced

    This date is part of the supplied schedule; a topic has not yet been provided.

    Details to come

  5. Data Cleaning

    Preparing inconsistent or incomplete data for reliable analysis.

    Topic announced

  6. Descriptive Analysis

    Using summary measures to understand the shape and meaning of a dataset.

    Topic announced

  7. Descriptive Analysis

    Continuing the analysis and interpretation of patterns in data.

    Topic announced

  8. Visualization

    Choosing clear visual forms that communicate evidence accurately.

    Topic announced

  9. Visualization

    Refining charts and using visual storytelling to explain findings.

    Topic announced

  10. Topic to be announced

    This date is part of the supplied schedule; a topic has not yet been provided.

    Details to come

  11. Topic to be announced

    This date is part of the supplied schedule; a topic has not yet been provided.

    Details to come

  12. Variability

    Understanding how and why values differ within a dataset.

    Topic announced

Skills and topics

Skills developed through study and instruction

Students build practical skills across programming, data analysis, AI literacy, and communication.

Programming foundations

Write Python, work in VS Code and Google Colab, and use NumPy and pandas.

Data analysis

Clean data, use Pandas DataFrames, find patterns, and communicate results through visualization.

AI literacy

Explore machine learning, generative AI, large language models, transformers, deepfakes, and bioinformatics.

Teaching and communication

Turn technical questions into clear explanations, useful results, and lessons that can be shared with others.