(2024)
This NSF-funded summer program teaches students the principles of data science and machine learning. Students will learn concepts about data modeling, data cleaning, data wrangling, and visualization. Students will learn basic Python programming for processing data and learn ML techniques, including basic concepts, training, classification, and sentiment analysis.
The program will use the open-source Texera platform to help students get familiar with these concepts even if they have a limited computing background. We will include a capstone project for students to learn these skills by analyzing real data (e.g., social media data) to apply the knowledge to conduct ML-based data science. The instructors and staff include professors and Ph.D. students from UCI and UCLA who are experts in data management, data science, and machine learning.
Faculty Instructors
PhD Student Instructors
Yunyan Ding, Department of Computer Science, UCI
Anthony Cuturrufo, Department of Computer Science, UCLA
Alexander Kundu Taylor, Department of Computer Science, UCLA
program Details
- Program time: 07/08/2024 – 07/19/2024
- Daily Schedule: From 9 AM to 4 PM
- Location: UCI Campus
- Instruction Format: The program will consist of both lectures and lab sessions.
- Fees: Free of charge (funded by NSF)
- Lunch: Lunch will be provided during the program.
- Deadline to apply: 04/15/2024 by 11:59PM (Closed)
- Acceptance notification: Before 05/15/2024
- Eligibility: Current sophomores (10th graders) and current juniors (11th graders)
- Prerequisites: Algebra II or Integrated Math II
- Contact email:
Program Schedule
| Date | Day | Morning (Lecture) | Afternoon (Lab) | Slides |
| 7/8/24 | 1 | Program Overview; Texera Platform Overview; Construct the 1st Data Analytics Workflow on Texera | Form teams; Project topic discussion | Slide01 |
| 7/9/24 | 2 | Data and data wrangling concepts; Data science operators – Scan, Projection, Type Cast, Sort, Filter | Collaborative project development in each team | Slide02 |
| 7/10/24 | 3 | Data science operators – Union, Distinct, Intersection, Diff, Aggregate, Join; Python basics; Python UDF tuple API basics | Collaborative project development in each team | Slide03 |
| 7/11/24 | 4 | Python intermediate; Python UDF tuple API exercise; Python UDF table API basics | Collaborative project development in each team | Slide04 |
| 7/12/24 | 5 | Python advance; Python UDF table API exercise; Machine Learning introduction and hands-on practice using ML operators | Collaborative project development in each team | Slide05 |
| 7/15/24 | 6 | Introduction to AI; Classification | Collaborative project development in each team | |
| 7/16/24 | 7 | Machine Learning Foundations; Linear Regression | Collaborative project development in each team | |
| 7/17/24 | 8 | Neural Networks | Collaborative project development in each team | |
| 7/18/24 | 9 | Computer Vision, Probability, Natural Language Processing | Collaborative project development in each team | |
| 7/19/24 | 10 | ChatGPT: learn how to play around with it | Project Showcase |
