CIS 4394 Agentic AI · Fall 2026 · Dr. Xinyu Fu
CIS 4394 Agentic AI · Fall 2026 · Dr. Xinyu Fu
Generative AI is evolving into agentic AI — systems that reason, plan, adapt, and collaborate in complex environments. This course teaches the foundations and the practice: from the agent loop and tool use to evaluation, safety, and deployment, ending in a real capstone agent.
A 4-day online bootcamp run by the Centre for Effective Altruism for people who want to steer their career toward the world’s biggest problems. AI safety is one of its main tracks, alongside pandemic preparedness and global development. You get structured decision frameworks for comparing directions, 1:1 written and verbal feedback from advisors, peer accountability, and sessions with people who left tech, government and business to work on AI safety and related fields.
Cost: free — donors cover it. Online. Two options: weekdays Oct 12–15, or weekends Oct 17–18 & 24–25. About 20–30 hours total; two interactive calls a day (8 am and 4 pm GMT — the 4 pm GMT call is noon in Atlanta). Graduates can opt into an accountability buddy and follow-up 1:1 career advising.
Who it is for — read this honestly: it is aimed at accomplished professionals; most participants have 5+ years’ experience, though the organizers say that is “not required.” You must be 18+, and entry is competitive. If you are still an undergraduate, apply if you have a track record you can point to — internships, shipped projects, your capstone from this course — and do not take a “no” personally; it is a mid-career-leaning program. There is also a version specifically for operations professionals and organizational leaders (same form; you state your preference).
Apply: a 15-minute form, no interview — forms.cea.community/bootcamp ↗ · full details and FAQ: effectivealtruism.org/courses/bootcamp ↗
GA2 is released on iCollege: build a tool-using agent — a loop, at least two tools with real schemas, a max-iteration guard, one execution trace, and a one-page design note. Submitted as a group, and you self-enroll (Assessments → Groups → the GA2 category → View Available Groups → Join Group), in your own section.
These are new groups — your GA1 team does not carry over, and you are encouraged to team up with people you have not worked with yet. Code path, no-code path, or your own favourite tool — all graded on the same standard. Due in Week 7; check iCollege for your section’s due date.
Enrollment steps, the three build paths, and what every path must show: Week 5 Summary →
Due this week (Week 6). The proposal assignment is open on iCollege — the official instructions and rubric are there. Submit to your own section — the two sections’ deadlines are a day apart, so check iCollege for your section’s due date.
Tip: before you choose a model for your project, measure it — Week 5, page 03 shows how to test a local model over several runs.
The Association for Information Systems (AIS) GSU Student Chapter hosts an interactive panel with consultants from Capgemini — the skills that stand out in today's market, a day-in-the-life view of consulting, and direct networking. Open to all CIS students.
Details and RSVP on PIN: AIS chapter page ↗ · Browse PIN events ↗
Each week ships as an interactive mini-site: clickable architecture explorers, step-through agent-loop simulators, live concept checks, hidden answers on every question, and full lab instructions. Readings and quiz scope are listed at the end of each week.
LLMs → agents, the loop, agentic coding, prompting & context engineering, reasoning & planning.
Tool use and function calling, MCP & A2A, memory & RAG.
Evaluation & reliability, multi-agent systems, security & governance.
Deployment & agentic commerce, capstone studios, final presentations.
Introduction to Agentic AI + What Enterprises Actually Use (PowerPoint, ~66 slides, with speaker notes and references).
Download .pptx ↓Lesson deck, step-by-step lab guide, starter kit (résumé, preferences, six-job dataset with a prompt-injection test, Python baseline), and pre-class prep.
Download .zip ↓Four short Python scripts for a tool-calling agent on a local model: the raw agent loop, a pass^k runner, the same agent in LangGraph, and the tool-design experiment. No API key needed.
Download .zip ↓Instructor, Computer Information Systems, J. Mack Robinson College of Business, Georgia State University. This course pairs research-grounded foundations (ReAct, Toolformer, LLM-agent surveys, τ-bench) with what enterprises actually deploy — and every claim on these pages is dated and sourced, because agentic AI moves fast. The course is offered within PATH — Pathways for AI Training & Hiring, a national initiative led by MIT RAISE and Georgia State.
Faculty profile ↗ · Personal site ↗ · xfu11 [at] gsu [dot] edu
Agent loops, autonomy, and control flow are abstract until you can push on them. Each week's site turns the core abstractions into things students can click, step through, and break — the same standard the course applies to agents themselves: don't trust the demo, test the behavior.