MSBAi Curriculum: Single Source of Truth
Program: Master of Science in Business Analytics - Online (MSBAi) Institution: Gies College of Business, University of Illinois Launch: Fall 2026 Total Duration: 18 months (4 semesters + 1 summer) Total Credits: 36 Format: 8-week courses within 16-week semesters Common Thread: Python + Jupyter Notebooks across all courses
Pre-Program Requirements
Before enrolling, all MSBAi students must complete:
- Inferential Statistics (Coursera — Duke University or equivalent)
- Basic Statistics (Coursera — University of Amsterdam or equivalent)
These are the same statistics prerequisites used by the on-campus MSBA program. Students should complete these before FIN 550 (Fall 2026, Weeks 9-16). Completion is verified during onboarding.
Program Timeline
Year 1
Fall 2026 Semester (16 weeks)
| Course | Credits | Weeks | Instructor | Notes |
|---|---|---|---|---|
| BADM 554 - Data Foundations | 4 | Weeks 1-8 | Vishal | SQL, Python, databases, ETL pipelines |
| BDI 513 - Data Storytelling | 4 | Weeks 5-12 | Ron | Straddles both halves - visualization, narrative, financial analysis |
| FIN 550 - Predictive Analytics for Business (ML I) | 4 | Weeks 9-16 | Supervised ML: regression, classification, feature engineering, business case | |
| Semester Total | 12 |
Student Experience:
- Weeks 1-4: BADM 554 only (foundations)
- Weeks 5-8: BADM 554 + BDI 513 (overlap)
- Weeks 9-12: BDI 513 + FIN 550 (overlap)
- Weeks 13-16: FIN 550 only (finish strong)
Spring 2027 Semester (16 weeks)
| Course | Credits | Weeks | Instructor | Notes |
|---|---|---|---|---|
| BADM 558 - Big Data Infrastructure | 4 | Weeks 1-8 | Ashish | AWS, Spark, dbt, Redshift + Snowflake, data engineering with Python |
| Generative AI for Analytics | 2 | Weeks 5-8 | TBD | RAG, agentic AI, LangChain, prompt engineering, AI governance |
| Quantum Computing for Optimization | 2 | Weeks 9-12 | Abhijeet | Business-focused quantum fundamentals, simulators |
| Semester Total | 8 |
Student Experience:
- Weeks 1-4: BADM 558 (4 cr) only
- Weeks 5-8: BADM 558 (4 cr) + GenAI (2 cr) = 6 credits simultaneously
- Weeks 9-12: Quantum Computing (2 cr) only - lighter load
- Weeks 13-16: Open (no courses)
Summer 2027 (8 weeks)
| Course | Credits | Weeks | Instructor | Notes |
|---|---|---|---|---|
| BADM 557 - Decision Intelligence with AI | 4 | Weeks 1-8 | Gautam | Case studies, BI, Power BI + Python, AI-augmented decisions |
| Summer Total | 4 |
Cumulative after Summer 2027: 24 credits
Year 2
Fall 2027 Semester (16 weeks)
| Course | Credits | Weeks | Instructor | Notes |
|---|---|---|---|---|
| BADM 576 - Data Science & Machine Learning (ML II) | 4 | Weeks 1-8 | Zilong | Advanced ML: ensembles, unsupervised, NLP, time series, neural nets, MLOps/LLMOps |
| Specialization Elective | 4 | Weeks 9-16 | TBD | Finance, Healthcare, Marketing, or Data Engineering track |
| Semester Total | 8 |
Cumulative after Fall 2027: 32 credits
Spring 2028 Semester (first 8 weeks only)
| Course | Credits | Weeks | Instructor | Notes |
|---|---|---|---|---|
| Capstone/Practicum | 4 | Weeks 1-8 | TBD | Portfolio + client project |
| Semester Total | 4 |
Program Total: 36 credits
Credit Breakdown
Core Courses (24 credits)
| # | Course | Credits | Semester |
|---|---|---|---|
| 1 | BADM 554 - Data Foundations | 4 | Fall 2026 |
| 2 | BDI 513 - Data Storytelling | 4 | Fall 2026 |
| 3 | FIN 550 - Predictive Analytics for Business (ML I) | 4 | Fall 2026 |
| 4 | BADM 558 - Big Data Infrastructure | 4 | Spring 2027 |
| 5 | BADM 557 - Decision Intelligence with AI | 4 | Summer 2027 |
| 6 | BADM 576 - Data Science & Machine Learning (ML II) | 4 | Fall 2027 |
Required Electives (8 credits)
| # | Course | Credits | Semester |
|---|---|---|---|
| 7 | Generative AI for Analytics | 2 | Spring 2027 |
| 8 | Quantum Computing for Optimization | 2 | Spring 2027 |
| 9 | Specialization Elective | 4 | Fall 2027 |
Capstone (4 credits)
| # | Course | Credits | Semester |
|---|---|---|---|
| 10 | Capstone/Practicum | 4 | Spring 2028 |
Faculty Assignments
| Course | Instructor | Semester |
|---|---|---|
| BADM 554 - Data Foundations | Vishal | Fall 2026 |
| BDI 513 - Data Storytelling | Ron | Fall 2026 |
| FIN 550 - Predictive Analytics for Business (ML I) | Fall 2026 | |
| BADM 558 - Big Data Infrastructure | Ashish | Spring 2027 |
| Generative AI for Analytics | TBD | Spring 2027 |
| Quantum Computing for Optimization | Abhijeet | Spring 2027 |
| BADM 557 - Decision Intelligence with AI | Gautam | Summer 2027 |
| BADM 576 - Data Science & Machine Learning (ML II) | Zilong | Fall 2027 |
| Specialization Elective | TBD | Fall 2027 |
| Capstone/Practicum | TBD | Spring 2028 |
Key Design Rules
1. 8-Week Courses in 16-Week Semesters
- Each course is 8 weeks long (half a traditional semester)
- Students take 2-3 courses per semester
- Courses can run in first half (weeks 1-8), second half (weeks 9-16), or straddle both (e.g., weeks 5-12)
2. Week Numbering Resets Each Semester
- Fall 2026: Weeks 1-16
- Spring 2027: Weeks 1-16
- Summer 2027: Weeks 1-8
- Fall 2027: Weeks 1-16
3. Straddling Courses
- BDI 513 (Fall 2026): Weeks 5-12 (straddles Fall 1 + Fall 2)
- Starts week 5 when BADM 554 content is established
- Ends week 12 before FIN 550 ramps up
4. Credit Distribution by Semester
- Fall 2026: 12 credits
- Spring 2027: 8 credits
- Summer 2027: 4 credits
- Fall 2027: 8 credits
- Spring 2028: 4 credits
This is the single source of truth for all program-level facts. All other documents should reference this file rather than duplicating program parameters.
Last Updated: February 2026