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MSBAi Standard Tools Reference

Audience: Faculty, course designers, and TAs. This page defines the standard toolset for all MSBAi courses. Students receive a streamlined setup guide during onboarding.

Tool Stack Overview

1. VS Code — Primary IDE

What: Free, open-source code editor from Microsoft. Extensible with thousands of plugins.

Why VS Code (not JupyterLab): VS Code is where professional developers and data scientists work. It supports notebooks, Python scripts, terminal, Git, debugging, and AI tools in one environment. Ron Guymon: “This is more complex than JupyterLab, but ultimately more useful. I think the students will have more appetite for it.”

Install: code.visualstudio.com

Required extensions for MSBAi:

2. GitHub Copilot Pro — AI Coding Assistant

What: AI pair programmer built into VS Code. Provides inline code completions, chat, and autonomous agent mode.

Cost: Free for verified students for 1 year (normally $10/month). Full Copilot Pro — no feature restrictions.

Note (2026-05-21): GitHub Copilot student free plan signups are currently paused. The program is evaluating program-funded vs. student-purchased AI access as alternatives. Google Colab’s built-in AI assistance is available as an interim fallback. This page will be updated once the AI access model is confirmed. (See OPEN_QUESTIONS.md — “AI access model: program-funded vs. student-purchased.”)

How to get it (once signups resume or program-funded access is confirmed):

1. Create a GitHub account at github.com
2. Apply for the GitHub Student Developer Pack using your @illinois.edu email
3. Verify student status through GitHub Education
4. Go to GitHub Settings → Copilot → sign up for free
5. Install the GitHub Copilot extension in VS Code

What students get with Copilot Pro:

Low floor / high ceiling progression:

Week 1-2:   Inline completions only (ghost text while typing)
Week 3-4:   Copilot Chat for debugging and explanations
Month 2+:   Agent Mode for multi-step tasks
Capstone:   Custom instructions, agent skills, MCP integrations (see courses/practicum.md)

Faculty note: Copilot is a tool, not a shortcut. All courses include AI attribution requirements — students must document what AI tools they used, what prompts they gave, and how they validated outputs. See design/assessment_strategy.md.

3. Google Colab — Notebook Environment

3a. Colab in Browser (Low Floor)

What: Free, browser-based Jupyter notebook environment with cloud compute (including free-tier GPU).

Why it’s the floor: Zero install. Students open a browser, sign in with Google, and start coding. No Python setup, no dependency management, no terminal.

URL: colab.research.google.com

Free-tier includes:

• Python environment with common libraries pre-installed (pandas, sklearn, matplotlib, etc.)
• NVIDIA T4 GPU and TPU v5e accelerators (limited session time)
• Google Drive integration for file storage
• Shareable notebooks via link

When to use browser Colab:

• Pre-program orientation and bridge modules
• First 1-2 weeks of any course (before VS Code setup is complete)
• Quick prototyping and experimentation
• Students who need a fallback when VS Code has issues

3b. Colab Extension for VS Code (High Ceiling)

What: Official Google extension that connects .ipynb notebooks in VS Code to Colab cloud runtimes. Launched November 2025.

Why it matters: Students get VS Code’s full IDE features (Copilot, debugging, Git, extensions) while running code on Colab’s cloud GPUs. Best of both worlds.

Install: VS Code Marketplace

How it works:

1. Open any .ipynb file in VS Code
2. Click “Select Kernel” → choose “Colab”
3. Sign in with Google account
4. Code runs on Colab runtime; results display in VS Code

Current limitations (as of Feb 2026):

• Cannot mount Google Drive (use Git repos or cloud storage for datasets)
• Colab Secrets not available (use environment variables or .env files)
• Session timeouts same as browser Colab (reconnect as needed)

Faculty note: Assignments should be .ipynb files stored in GitHub repos. This works identically whether students use browser Colab or the VS Code extension. Do not design assignments that depend on Google Drive mounting.

4. Google Gemini Pro — AI Research & Writing

What: Google’s most capable AI model with research, writing, and productivity features.

Cost: Free for verified students for 1 year (normally $19.99/month). Full Google AI Pro plan.

How to get it:

1. Go to gemini.google/students
2. Sign up with a personal Gmail account (not @illinois.edu)
3. Verify student status through SheerID
4. Sign up by April 30, 2026

What students get:

Faculty note: Gemini is complementary to Copilot. Copilot is for coding (inside VS Code). Gemini is for research, writing, and analysis (browser-based). Students should use both. Deep Research is particularly valuable for project background research and literature reviews.

5. Claude / ChatGPT — General AI Assistants

What: General-purpose AI assistants for explanation, debugging, brainstorming, and writing.

Cost: Free tiers available for both. Students may also access these through Copilot’s model selector.

MSBAi policy: No vendor lock-in. Course materials should reference “AI tools” generically. When demonstrating specific features, show at least two platforms. Students choose their preferred tools and document usage in AI attribution logs.

6. GitHub — Version Control & Portfolios

What: Code hosting platform with version control, collaboration, and CI/CD.

Cost: Free. Students also get the Student Developer Pack with additional tools.

MSBAi requirements:

• All project code in GitHub repos (public for portfolio)
• Professional README files for all projects
• Commit history shows individual contribution (used in team project assessment)
• GitHub profile becomes the student’s professional portfolio

Student Developer Pack includes:

• GitHub Copilot Pro (see above)
• GitHub Codespaces (60 hours/month cloud dev environments)
• Free .me domain (Namecheap)
• Various cloud credits and tool access

7. BI / Visualization Tool — Course-Level Choice

No program-wide BI tool is mandated. Faculty select the tool appropriate for their course:

• Power BI Desktop — free, academic license via Illinois. Good for executive-style dashboards.
• Tableau — available via Illinois site license.
• Python (plotly, streamlit, dash) — preferred in code-first courses (BADM 554, FIN 550, BADM 576).
• AI-native visualization — BADM 557 uses AI-generated charts and frameworks; no dedicated BI tool required.

Faculty should document their tool choice in their course syllabus.

8. WRDS — Financial & Accounting Data

What: Wharton Research Data Services. Access to Compustat (firm financials), CRSP (stock returns), and other research databases.

Cost: Program-paid annual license (College expense, not student expense).

Used in: FIN 550 (primary), potentially other courses.

Faculty note: WRDS access should be used alongside open datasets and APIs (yfinance, SEC EDGAR, Kaggle, Census Bureau) so students learn both licensed and open data workflows. Having WRDS as a program-wide resource is a branding differentiator — “Gies provides access to institutional-grade financial data.”

9. GCP — Cloud Data Platform

What: Google Cloud Platform, specifically BigQuery (serverless data warehouse) and supporting GCP services (GCS, Cloud Functions).

Cost: Free tier (BigQuery: 10 GB storage + 1 TB queries/month free). No credit card required for basic use; GCP free tier sufficient for course projects.

Used in: BADM 554 (BigQuery for SQL, ETL deployment), BADM 558 (BigQuery + Snowflake + full GCP stack)

Why BigQuery over Cloud SQL: Serverless — no instance to provision or manage. Browser-accessible via GCP console. Columnar warehouse model aligns with analytics use cases across both courses. Consistent GCP thread from first course (BADM 554) through data engineering (BADM 558).

Proposed Tools (Under Evaluation — Not Yet Adopted)

These tools are being evaluated for possible use in MSBAi courses. They are not part of the standard toolset and have not been formally vetted. Faculty should not assign them until they are moved to the confirmed stack above.

10. Mindforum — Collaborative AI Workspace (Proposed)

What: A shared workspace for small groups (2–6 participants) with an AI collaborator that only speaks when explicitly mentioned with @ai. Groups can upload documents as context — readings, datasets, case studies, project briefs.

URL: mindforum.illinihunt.org

Cost: Free (Gies infrastructure). No install required — browser-based.

When to use in class:

Design principle: The @ai mention model enforces the pre-AI/post-AI discipline — students must decide when to invoke AI, rather than having it generate responses automatically. This aligns directly with AIAS Level 2–4 design and the Critical Engagement principle.

Faculty note: Mindforum is most powerful when the group is doing genuine deliberation before invoking @ai. Assign tasks where the human discussion itself is the first deliverable — @ai is called to challenge, extend, or evaluate, not to start.

11. Cognitive Swarm — Real-Time Group Brainstorming (Proposed)

What: A multimodal brainstorming application for large groups. Participants voice ideas; AI extracts concepts and positions them in 3D space by semantic similarity. Three background agents run simultaneously (connection-finder, critic, direction-suggester). Groups vote using quadratic voting, then synthesize top ideas into a diagram.

URL: agentlab.illinihunt.org/cognitive-swarm

Cost: Free (Gies infrastructure). Browser-based, real-time.

Three phases:

1. Explore — participants speak ideas; AI anchors concepts in semantic space; background agents find connections, critique weak reasoning, and suggest new directions
2. Vote — quadratic voting: fixed credit budget per participant; extra votes on the same idea cost progressively more, preventing any single voice from dominating
3. Forge — system synthesizes top-weighted ideas into a shareable diagram (flowchart, mindmap, ER diagram, or journey map — format inferred from topic)

When to use in class:

Pedagogical notes:

• Quadratic voting is itself a curriculum topic — a decision-making mechanism worth naming explicitly. Students learn about it by using it.
• The three background agents (connector, critic, direction-suggester) are a live multi-agent system. In Agentic AI, flip the sequence: use it first, then deconstruct the architecture.
• Voice input lowers the barrier to participation for students who hesitate to type in group settings.
• The Explore → Vote → Forge sequence enforces the diverge-before-converge discipline that Studio sessions aim for.

Student Onboarding Checklist

This is the setup sequence for new MSBAi students during pre-program orientation:

Total setup time: ~60 minutes (excluding bridge module)

Fallback: If GitHub Education verification is delayed or Copilot student signups remain paused, students use Colab in browser (which has AI assistance built-in) until the program-funded AI access model is confirmed.

Local install fallback — Illinois Anywhere: Students who cannot install software on their primary work computer (e.g., employer-managed devices) can access a virtual Windows machine through the Illinois Anywhere service, which will have the required tools pre-installed. No action needed for most students; flagged during onboarding if local install is blocked.

Low Floor / High Ceiling: See DESIGN_PRINCIPLES.md Principle 3 for the full progression map from Colab (zero install) to VS Code + Copilot Agent Mode.

Faculty Guidelines

When designing course materials:

1. Assignments must be .ipynb files in GitHub repos. This works for both browser Colab and VS Code users.
2. Do not depend on Google Drive mounting. Use Git repos, direct downloads, or API calls for data access.
3. Reference “AI tools” generically in syllabi. When demonstrating, show Copilot for coding tasks and Gemini/Claude for research/writing.
4. Include AI attribution requirements in all project rubrics. Template in design/assessment_strategy.md.
5. Studio sessions should demo VS Code + Copilot workflows — this is where students see the tools in action and build fluency.
6. Bridge modules handle setup. Courses can assume students have VS Code, Copilot, and Colab working by Week 1.

Tool support responsibilities:

This is the standard tools reference for the MSBAi program. All course technology stacks should align with this page. For program-level details, see program/curriculum.md. For assessment policies around AI tool usage, see design/assessment_strategy.md.