Generative AI Engineering
Build LLM-powered products that actually work
About this program
Six months dedicated to building real applications on top of large language models. You'll move past prompt-engineering tricks into the engineering discipline of RAG architectures, evaluation harnesses, tool-use agents, fine-tuning, and cost/latency optimization. Every module ships working code, culminating in a portfolio project deployed publicly.
Student ratings
Exceptional — 395 verified Canadian graduates rated this program 4.8/5. Reviews emphasize the applied capstone, instructor responsiveness, and career outcomes.
- 5★334
- 4★49
- 3★8
- 2★2
- 1★2
Who this program is for
- →Working professionals moving into generative ai roles
- →Analysts, developers, and product people leveling up on applied AI
- →Canadian residents seeking a verifiable diploma credential
Topics you'll cover
6 modules across 6 months — 24 lessons in total.
Full syllabus
Module 1 · Month 1 — LLM Fundamentals▾
- L1How transformers actually work
- L2Tokenization and context windows
- L3Sampling: temperature, top-p, top-k
- L4Comparing frontier and open models
Module 2 · Month 2 — Prompt Engineering as Engineering▾
- L1Structured outputs and JSON mode
- L2Few-shot patterns that scale
- L3Prompt versioning and testing
- L4Chain-of-thought and self-consistency
Module 3 · Month 3 — Retrieval-Augmented Generation▾
- L1Chunking strategies
- L2Embedding models compared
- L3Vector databases: pgvector, Qdrant, Pinecone
- L4Hybrid and re-ranked retrieval
Module 4 · Month 4 — Agents and Tool Use▾
- L1Function calling primitives
- L2Planning patterns: ReAct, Plan-and-Execute
- L3Building safe tool surfaces
- L4Multi-agent orchestration
Module 5 · Month 5 — Fine-Tuning and Evaluation▾
- L1When to fine-tune vs. RAG
- L2LoRA and QLoRA
- L3Building eval harnesses with Promptfoo
- L4LLM-as-judge: when to trust it
Module 6 · Month 6 — Capstone▾
- L1Designing a real product
- L2Build sprint
- L3Deployment with usage metering
- L4Demo day
What you'll be able to do
- ●Design and ship a RAG application on a non-trivial corpus
- ●Build evaluation suites that catch regressions
- ●Architect multi-step agent systems with tool use
- ●Fine-tune open-weights models for a specific domain
- ●Reason rigorously about cost, latency, and quality trade-offs
Career paths after graduation
Frequently asked questions
How much does the Generative AI Engineering cost?▾
Tuition is $150 CAD, paid once. You can pay in full at checkout or choose an interest-free monthly plan. A 30-day refund window applies from your enrollment date.
How long is the Generative AI Engineering program?▾
Self-paced. Most students complete it in 6 months at roughly 8 hours per week, but you can go faster or slower — you keep lifetime access.
What are the prerequisites?▾
Python proficiency; Basic web development; Familiarity with REST APIs
Is the diploma recognized in Canada?▾
Yes. Graduates receive the Altaris AI Academy Diploma in Generative AI — a verifiable credential with a unique certificate number you can publish on LinkedIn and that any employer can verify at altarisai.org/verify.
What is the refund policy?▾
Full refund within 30 days of enrollment, no questions asked. After day 30, prorated refunds are available per our Refund Policy.
Who teaches the program?▾
Working Canadian AI practitioners — not academics. Every module is built and reviewed by a lead instructor working in the field today.
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