Notes in the Wiki.
Do you find yourself encountering data science tools that your research needs, but are unsure how to get started? Curious about the latest tools for organizing, visualizing and understanding your dataset? Are you looking for a better theoretical understanding of key concepts in statistical analysis?
Join us for this beginner-friendly, concept-focused, and practical introduction to the theory and practice of data science, from start to finish! Sessions cover topics such as data wrangling, statistics, visualization, exploratory data analysis, time series analysis, machine learning, natural language processing, deep learning, prompt engineering, and AI tools. Enhance your capabilities and take your data science research to the next level!
RESOURCES AND NOTES:
- REGISTRATION
- Data Science Essentials: From Jupyter to AI Tools
- We meet on Tuesdays at 3 PM in Weaver Science and Engineering Library Rm 212
- Zoom: https://arizona.zoom.us/j/86423223879
- There will be no workshop during Spring Break week.
- Content schedule and content are subject to change.
Date | Topic |
---|---|
01/16 | Introduction to Jupyter Notebooks |
01/23 | Data Wrangling 101: Pandas in Action |
01/30 | A Probability & Statistics refresher |
02/06 | A Probability & Statistics refresher |
02/13 | Data Visualization Libraries: Matplotlib |
02/20 | Data Visualization Libraries: Seaborn |
02/27 | Exploratory Data Analysis |
03/05 | Spring break |
03/12 | Time Series Analysis |
03/19 | Time Series Forecasting |
03/26 | Machine Learning with Scikit-Learn |
04/02 | Natural Language Processing |
04/09 | Deep Learning |
04/16 | Prompt Engineering |
04/23 | AI Tools Landscape |
Updated: 02/11/2024 (C. Lizárraga)
UArizona Data Lab, Data Science Institute, University of Arizona.