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Welcome to the Workshops wiki!
(Image credit: Anita Austvika, Unsplash+)
This series aims to provide a comprehensive introduction to data science using Python tools. Through eight one-hour sessions, you will gain hands-on experience in analyzing various types of data, such as numbers, text, time-series, images, and videos. These workshops are designed to equip you with the necessary skills and knowledge for academic and professional growth in data science. Your participation in these workshops will improve your understanding of the subject and allow you to connect with peers and experts from different fields. Learning Objectives
- To impart a foundational understanding of data science methodologies and techniques.
- To facilitate hands-on experience with Python libraries such as Pandas, NumPy, and Matplotlib.
- To enable graduate students to analyze and interpret diverse types of data, including numeric, textual, time-series, image, and video data.
- Introduction to Python for Data Science
- Data Wrangling 101: Pandas in Action
- Statistical Inference: The Backbone of Data Science
- Machine Learning Basics: Scikit-learn Unveiled
- Natural Language Processing: Text Mining and Sentiment Analysis
- Time Series Analysis
- Deep Dive into Deep Learning
- Computer Vision: Image Analysis
- A SQL Masterclass Part 1&2
- Introduction to Big Data with Apache Spark
- How to build data apps using Streamlit
Updated: 10-04-2023
UArizona DataLab, Data Science Institute, University of Arizona, 2024.
