Program Overview

Program Overview

The Immersive Program in Data Analysis is designed to equip students with the skills and knowledge necessary to thrive in the digital economy. This full-time, in-person certificate program focuses on developing proficiencies in data collection, processing, visualization, and interpretation.

Program Details

• Duration: The program runs from August 19 to December 18, with a priority deadline of April 3, 2026, and a final deadline of June 5, 2026.
• Total Program Cost: $11,375 (USD), which includes course tuition, housing advice, visa support, orientation, program support, professional skills workshops, community-building events, and access to campus services.
• Fees Excluded: Textbooks, supplies, travel and housing costs, meals, daily expenses, and comprehensive health insurance.

Admission Requirements

To participate in this program, applicants must meet the following minimum requirements:

• Minimum Academic Requirements: Three years of undergraduate coursework with a GPA of 3.0.
• Minimum English-Language Proficiency Requirements: Official evidence of English-language proficiency, with accepted tests including TOEFL, IELTS, DAAD, TEM-4 or TEM-8, Cambridge C1 Advanced, and Duolingo.

Learning Outcomes

Upon completing the program, students will be able to:

• Use data wrangling and exploration methods to find meaning and patterns in structured data sets.
• Create descriptive, predictive, and prescriptive models for knowledge discovery with structured data sets.
• Perform decision analysis using optimization methods, operational research, management science, and spreadsheet analytics.
• Interpret results and use data visualization techniques to communicate findings to stakeholders.

Core Courses

The curriculum comprises five core courses, totaling 9 semester units (135 hours of instruction):

• Introduction to Data Analytics: Formulate and apply descriptive, predictive, and prescriptive analytics to guide decision-making in various industries.
• Data Visualization: Learn theoretical and practical elements to support a holistic approach to understanding data visualization.
• Python for Data Analysis: Build experience with statistical analysis using the Python programming language.
• Data Warehousing and Business Intelligence: Gain an understanding of data modeling, data warehousing, and SQL.
• Data Analytics Capstone: Complete a data analytics project that centers on a real-world problem.

Program Structure

• Session 1 (August–October): Introduction to Data Analytics, Data Visualization, and Data Analytics Capstone.
• Session 2 (October–December): Data Warehousing and Business Intelligence, Python for Data Analysis, and continued work on the Data Analytics Capstone.

Instructors and Networking

• Instructors: Seasoned industry professionals with extensive experience and exclusive ties to leading companies and organizations in the field.
• Networking Opportunities: Attend community-building events, professional skills workshops, and take advantage of the program's location in the Bay Area to network with peers and professionals.

Beyond the Classroom

• Professional Skills Workshops: Develop practical skills to prepare for careers in the business world.
• Sightseeing and Exploration: Take advantage of the program's location to explore the Bay Area, attend events on campus, and enjoy the local culture.

Eligibility for OPT

Upon successful completion of the program, students may be eligible for Optional Practical Training (OPT), allowing them to work in the United States for one year in a field directly related to their area of study.