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: 15 months (3 semesters + 1 summer) Total Credits: 36 Format: 8-week courses within 16-week semesters Common Thread: Python + Jupyter Notebooks across all courses STEM Designation: Not STEM designated (pending formal confirmation with Lorena — tracked in the internal open-questions registry; ask K-ai)


Course Production Status

This page does not track course status. Video and activity production status comes from the learning-design team’s Box rosters, synced automatically: BADM 554, BDI 513, FIN 550. Courses without a Box roster have no tracked status; ask K-ai for the latest decisions on them.


Preparatory Coursework (Staggered Model — Confirmed 2026-05-18)

Preparatory coursework is staggered, with each module timed to the first course that applies it. Two tiers:

Required, proof of completion (gated by registration hold)

Module Deadline Notes
GitHub + VS Code prep (DataCamp) Before Day 1 (BADM 554 Week 1) Foundational environment setup; required for all students
Gen AI literacy module End of Week 4 Self-study Canvas course; can run in parallel with BADM 554; required for all students. Students upload the completion certificates of the four AI literacy modules to the Module 9 Progress Check in MSBAi Essentials (Source of Truth doc comment, 2026-09-01, Cheng Li)

Self-diagnostic (ungated, completion not required)

Pattern: each downstream course with a self-diagnostic prep need gets its own numbered module in MSBAi Essentials, timed to that course’s start — this is an extending sequence (Module 10, 11, 12, …), not a fixed pair. As of the live Canvas course (verified 2026-08-16), Modules 10 and 11 are built and published; further courses’ prep (e.g. Quantum’s Linear Algebra prep below) is decided but not yet built into a numbered module.

Module Self-assessment by Notes
Python & Tools prep (Introduction to Applied Business Analytics, Coursera) Before BDI 513 start (Fall 2026 Week 5) Course selected (named in MSBAi Essentials Canvas Module 10: BDI 513 Skill Prep Course — self-assessment + course link; per Ron Guymon). Replaces the prior DataCamp plan (DataCamp retained for GitHub prep only). Linked from a Canvas self-assessment module — content stays on Coursera, not migrated into Canvas. Quiz indicates whether the student should work through the prep course; scores not evaluated by the program
MSBAi Stats Prep Course (private Coursera MOOC; Cheng Li) Before FIN 550 start (Fall 2026 Week 9) Purpose-built private course covering descriptive statistics, probability, sampling, hypothesis testing, regression. Named in MSBAi Essentials Canvas Module 11: FIN 550 Skill Prep Course (self-assessment + course link). Replaces the prior BADM 572 public MOOCs per “Stats prep delivery: private Coursera MOOC” (2026-06-10). Final naming/instructor-of-record pending. Self-diagnostic quiz only
Linear Algebra prep (platform/MOOC TBD; prep course lead: Maria Rodas) Before the Quantum Computing half of Quantum Approaches (Spring 2027 POT A; completed during Fall 2026 for Spring use) Prep for Quantum part 2 per the 2026-07-17 decision (internal registry; correcting the AY26-27 spreadsheet which mis-listed it under Agentic AI). Covers the quantum faculty’s required-knowledge list: vectors, matrices, eigenvalues/eigenvectors. Specific platform/MOOC TBD. Not yet built as a Canvas module — would be the next in the sequence (Module 12 or later) once ready

Source: internal decision registry (full records from K-ai) — “Preparatory coursework: staggered completion model” (2026-05-18); “Prep course module structure and delivery model” (2026-05-22); “BDI 513 Python & Tools prep: Coursera replaces DataCamp” (2026-05-22); “Stats prep delivery: private Coursera MOOC” (2026-06-10, supersedes the BADM 572 public MOOCs); “Linear Algebra prep belongs to Quantum (part 2), not Agentic AI” (2026-07-17). Module structure and names verified directly against the live MSBAi Essentials Canvas course (70398), 2026-08-16 — 12 modules published (0–11); corrects a 2026-06-13 audit that was read as a closed “Modules 10–11” set rather than an extending per-course sequence.

Target student: Career pivoters (age 25-40) from technical/STEM or non-analytics backgrounds. See program/target_profile.md for full profile and admission criteria.


Program Timeline

Soft launch dates (early student access ≈ 1 week before official start; source: registrar master schedule, mirrored in reference/msbai-schedule.md): BADM 554 Aug 17, 2026 · BDI 513 Sep 14, 2026 · FIN 550 Oct 12, 2026 · Quantum Approaches Jan 12, 2027 · BADM 558 Feb 8, 2027 · Agentic AI Mar 8, 2027 · BADM 557 May 10, 2027 · BADM 576 Aug 16, 2027 · Practicum Oct 11, 2027. Decision record: “Course soft launch dates” (internal registry — full record from K-ai).

Fall 2026 Semester (16 weeks)

Course Credits CRN Weeks Instructor Notes
BADM 554 - Enterprise Database Management 4 81817 Weeks 1-8 Vishal Sachdev SQL, Python, databases, ETL pipelines
BDI 513 - Data Storytelling 4 81818 Weeks 5-12 Ron Guymon Straddles both halves - visualization, narrative, financial analysis
FIN 550 - Big Data Analytics in Finance (ML I) 4 77523 Weeks 9-16 Xing Gao / Mathias Kronlund Supervised ML: regression, classification, feature engineering, business case
Semester Total 12        

CRNs are the Banner section numbers (section code BAI, cap 55/section), assigned for Fall 2026 registration. Source: registrar master schedule (Heather Aldridge), mirrored in reference/msbai-schedule.md. Later-term CRNs are still TBD.

Student Experience:


Spring 2027 Semester (16 weeks)

Course Credits Weeks Instructor Notes
Quantum Approaches for Decision Making 4 Weeks 1-8 Nathan Yang (Pt 1) / Abhijeet Ghoshal (Pt 2) Combined 8-wk course: Part 1 Quantum Cognition (wks 1-4, from Jan 19 / POT A), Part 2 Quantum Computing (wks 5-8, from Feb 15)
BADM 558 - Big Data Infrastructures 4 Weeks 5-12 Ashish Khandelwal Feb 15 start. GCP (GCS, Spark via Dataproc), dbt, BigQuery + Snowflake, data engineering with Python
Agentic AI 4 Weeks 9-16 Vishal Sachdev / TBD (adjunct hire pending) RAG, agentic systems, context engineering, evaluation of agentic systems, AI governance (LLMOps → BADM 576)
Semester Total 12      

Sequence revised 2026-06-01; POT dates confirmed 2026-06-02 (Maria Rodas with Ashish Khandelwal / Abhijeet Ghoshal / Nathan Yang; POT dates per Heather Aldridge, iDegrees): the two 2-cr quantum courses are combined into one 4-cr 8-week course (POT A start Jan 19, 2027), BADM 558 shifts to a Feb 15 start (wks 5-12), and Agentic AI starts Mar 15 (POT B). Course number is BADM 590 — a temporary number intentionally shared by both new courses (Quantum Approaches + Agentic AI) for year 1; permanent distinct numbers assigned later. MLK Day (Jan 18) falls the day before POT A — Week 1 live/studio scheduling TBD. Decision record: “Spring 2027 sequence revised” (internal registry — full record from K-ai).

Student Experience:

Concurrency note: the revised sequence creates two 8-credit concurrent stretches (wks 5-8, 9-12), heavier than the prior 6-cr symmetric design. Flagged for faculty deliverable-timing coordination in the wks 5-8 overlap (Quantum Pt 2 + BADM 558).


Summer 2027 (8 weeks)

Course Credits Weeks Instructor Notes
BADM 557 - Business Intelligence 4 Weeks 1-8 Gautam Pant Constructs-based BI, measurement frameworks, AI-augmented decisions
Summer Total 4      

Cumulative after Summer 2027: 28 credits


Fall 2027 Semester (16 weeks)

Course Credits Weeks Instructor Notes
BADM 576 - Data Science and Analytics (ML II) 4 Weeks 1-8 Zilong Liu / Amir Fazli Advanced ML: ensembles, unsupervised, NLP, time series, neural nets, MLOps/LLMOps
Practicum (BADM 550) 4 Weeks 9-16 Vanitha Virudachalam Portfolio + client project
Semester Total 8      

Program Total: 36 credits


Credit Breakdown

Core Courses (16 credits)

# Course Credits Semester
1 BADM 554 - Enterprise Database Management 4 Fall 2026
2 BDI 513 - Data Storytelling 4 Fall 2026
3 FIN 550 - Big Data Analytics in Finance (ML I) 4 Fall 2026
4 BADM 557 - Business Intelligence 4 Summer 2027

Advanced Courses (8 credits)

# Course Credits Semester
5 BADM 558 - Big Data Infrastructures 4 Spring 2027
6 BADM 576 - Data Science and Analytics (ML II) 4 Fall 2027

Required Electives (8 credits)

# Course Credits Semester
7 Quantum Approaches for Decision Making (Part 1: Quantum Cognition + Part 2: Quantum Computing) 4 Spring 2027
8 Agentic AI 4 Spring 2027

Practicum (4 credits)

# Course Credits Semester
9 Practicum (BADM 550) 4 Fall 2027

Catalog/Banner code BADM 550. Banner classifies the Practicum as Core (decision 2026-05-13); it is listed in its own section here for credit-structure clarity, not as a separate classification.


Faculty Assignments

Course Instructor Semester
BADM 554 - Enterprise Database Management Vishal Sachdev Fall 2026
BDI 513 - Data Storytelling Ron Guymon Fall 2026
FIN 550 - Big Data Analytics in Finance (ML I) Xing Gao / Mathias Kronlund Fall 2026
BADM 558 - Big Data Infrastructures Ashish Khandelwal Spring 2027
Quantum Approaches for Decision Making Nathan Yang (Part 1) / Abhijeet Ghoshal (Part 2) Spring 2027
Agentic AI Vishal Sachdev / TBD (adjunct hire pending) Spring 2027
BADM 557 - Business Intelligence Gautam Pant Summer 2027
BADM 576 - Data Science and Analytics (ML II) Zilong Liu / Amir Fazli Fall 2027
Practicum Vanitha Virudachalam Fall 2027

Key Design Rules

1. 8-Week Courses in 16-Week Semesters

2. Week Numbering Resets Each Semester

3. Straddling Courses

4. Credit Distribution by Semester


This is the single source of truth for all program-level facts. All other documents should reference this file rather than duplicating program parameters.