Global Education and Training (GET) is offering a 4-week online undergraduate summer school program: “Artificial Intelligence in Data Science," July 19 – August 13, 2021.
All interested, current undergraduate students from universities worldwide can apply. Prospective applicants must have excellent grades in their university courses. Program fee is $1000 per student, and group rates are available.
All classes in this course will be taught in English and will culminate with a final exam or presentation. Students who successfully complete the program will receive a certificate of recognition.
GET programs are non-degree in nature. Students will not receive any course credit from the University of Illinois Urbana-Champaign.
Key Program Dates
July 19: Teaching Assistant (TA) Led Reading Week
July 26: Network Analysis Lectures & TA Led Q&A
August 2: Data Science Creativity Lectures & TA Led Q&A
August 9: Co-Curricular Sessions & Final Projects
Online Program Format
Our online program format features synchronous lectures with top UIUC faculty members, and assignments and group projects are completed by students asynchronously.
Enrolled students must have access to Wi-Fi and a device (e.g., computer, laptop, or tablet) that is suitable for participation in online video conference sessions.
UIUC Faculty Information
Jana Diesner, PH.D (Associate Professor, School of Information Science)
At UIUC, Jana leads the Social Computing lab. Her research in computational social science and human-centered data science combines methods from natural language processing, social network analysis, and machine learning with theories from the social sciences to advance knowledge and discovery about interaction based and information-based systems.
She brings her research into the application contexts of responsible computing (transparency, governance, biases, and ethics of computing), crisis informatics, and impact assessment. She is currently serving as the Director for Strategic Initiatives / Data Science at her unit.
Wade Fagen-Ulmschneider, PH.D (Teaching Associate Professor, Siebel Center for Computer Science)
With a passion for data, Wade often teaches thousands of students each year in his courses on Data Structures, Data Visualization, and Data Science. He was selected as one of the National Academy of Engineering’s Frontiers of Engineering Education scholars, awarded the Collins Award for Innovation Teaching, and has been consistently ranked as an excellent instructor by his students for the past ten years.
His work on data visualizations has been used by governors of multiple states, featured by websites including Popular Mechanics and The Verge, and has been viewed by millions of readers.
Network Analysis (10 Hours)
Students will be introduced to fundamental theories, concepts, methods, and applications of network analysis. Students learn how to approach network analysis tasks and projects in an informed and analytical fashion. Students acquire practical hands-on skills in collecting, analyzing, and visualizing network data. At the end of the course, students will be able to critically assess network studies and to solve real-world, network-centric problems.
Data Science Creativity (10 Hours)
Students will be introduced to Python, data visualization, visual encoding, data generation: sampling and simulation, identification, clustering, and classification, etc. Students will perform hands-on-analysis of real-world datasets to analyze and discover the impact of the data.
Co-Curricular Sessions (4 Hours)
Enriching students' experiences by providing interactive resources for planning their U.S. education overseas. Learn more about GET’s co-curricular sessions.
Session topics include:
Virtual campus tour
Admission requirements & graduate program introduction
Writing a graduate school personal statement
How to be a successful graduate student
Contact Our Team
Meng Liu (GET Program Coordinator), email@example.com
Joanna Hu (Program Specialist - Shanghai Office), firstname.lastname@example.org
Karen Weng (Senior Representative - Shanghai Office), email@example.com