AIINFRA 303 is the culminating capstone of the AI Infrastructure and Architecture certificate sequence. Students design, build, deploy, and present a complete production-grade AI system of their own scoping — integrating compute, containers, cloud infrastructure, and a model or agent layer end to end. The course emphasizes professional practice: architecture documentation, infrastructure as code, CI/CD automation, security and observability, and a polished portfolio artifact suitable for employer review.
54 contact hours (3-unit equivalent), delivered over a 16-week term at approximately 3.4 hours/week. This is a non-credit course on the CDCP Certificate of Completion pathway.
AIINFRA 100–302 — completion of the full certificate sequence is required prior to enrollment in this capstone course.
| Week | Topic |
|---|---|
| 01 | Capstone Kickoff: Scoping a Production AI System |
| 02 | Requirements, Success Metrics, and Architecture Decision Records |
| 03 | System Architecture and Full-Stack Infrastructure Design |
| 04 | Project Planning: Milestones, Risk, and a Reproducible Repository |
| 05 | Building the Core: Containerized Services and Environments |
| 06 | Deploying to the Cloud with Infrastructure as Code |
| 07 | A CI/CD Pipeline for Your Capstone |
| 08 | Design Review and Working Vertical Slice (Midterm) |
| 09 | The Model Layer: Serving, Adaptation, or RAG Integration |
| 10 | Adding Agentic and MCP or Retrieval Capabilities |
| 11 | Security, Guardrails, and Responsible-AI Hardening |
| 12 | Observability, Evaluation, and Cost Instrumentation |
| 13 | Load Testing, Right-Sizing, and Performance Tuning |
| 14 | Documentation, Runbooks, and Reproducibility |
| 15 | Portfolio Packaging, Demo Prep, and Technical Storytelling |
| 16 | Final Capstone Submission, Presentation & Course Review (Capstone) |
| Component | Weight |
|---|---|
| Labs | 40% |
| Discussions | 10% |
| Weekly Quizzes | 15% |
| Midterm | 15% |
| Final Capstone | 20% |
Credit/No-Credit. 70% overall is required to pass.
Academic integrity: All submitted work — code, documentation, and diagrams — must represent your own effort. You may use AI coding assistants and reference open-source code, but you must be able to explain and defend every design decision and every line of your capstone during review. Uncredited copying of a classmate's or another party's capstone architecture or code is a violation of the LACCD Student Conduct Code and will be referred accordingly. Late work: Weekly labs and quizzes are due as posted; a 10% per-day late penalty applies for up to 3 days, after which work receives no credit unless prior arrangements were made with the instructor. The Midterm design review and Final Capstone deadlines are fixed due to peer-review and presentation scheduling; extensions require documented emergency circumstances approved in advance. Responsible use of AI: This course assumes and encourages the use of AI tools (code assistants, LLMs, agents) as part of professional infrastructure practice. Students must disclose significant AI-assisted components in their capstone documentation and remain fully accountable for the correctness, security, and cost implications of anything AI-generated in their submitted system. Accessibility: This course complies with LACCD accessibility standards and Section 508/ADA requirements. Students needing accommodations should contact the campus Disabled Students Programs and Services (DSPS) office as early in the term as possible so accommodations can be arranged for labs, quizzes, and the capstone presentation.
All tools are free or free-tier. No paid software or paid cloud tier is required to complete this course.
Notion ID: 392c08fd-0278-811c-a107-c7559c4679d5 Notion URL: https://app.notion.com/p/392c08fd0278811ca107c7559c4679d5