v.2026.4 [LIVE]
Engineering Curriculum 2026
Foundations & Modern LLMs
Master the internals of modern LLMs. Understand how GPT-4o, Claude, and Gemini actually process tokens and how to architect systems around them using advanced prompting and structured outputs.
Syllabus Architecture
1
Session 01 IntensiveLive Lab
Session 1 — Modern AI System Internals
- Evolution of LLMs: From transformers to GPT-4o, Claude 3.5, and Gemini 1.5 Pro
- How LLMs actually work: tokenisation, temperature, sampling, top-p, stop sequences
- Context windows explained: what goes in, what gets lost (lost-in-the-middle phenomena)
- Comparing model capabilities: benchmarks vs real-world production performance
- AI system design patterns: direct API, wrapper service, and gateway proxies
- Latency budgets and cost modelling: calculating TCO per token across providers
- Theoretical Audit: Reading AI vendor documentation like a senior engineer
2
Session 02 IntensiveLive Lab
Session 2 — Advanced Prompting & Structured Logic
- Prompt engineering fundamentals: role prompting, few-shot examples, and chain-of-thought
- System prompts vs User prompts: defining 'unbreakable' personality and constraints
- Structured JSON outputs: response_format, strict mode, and Zod schema validation
- Prompt chaining: breaking complex tasks into reliable, sequential AI steps
- Common failure modes: hallucination, context stuffing, and prompt injection security
- Hands-on: building a reliable schema generator for unstructured data
Module Toolchain
Cohort 04 — Active Enrollment
Early Access Pricing
$1800
$3500Duration6 Weeks
Next CohortMay 5
Sessions2h 30m / session
Verified Applied Cohort 04 Graduation Path
Trusted by Engineering Teams
Verification Phase
Capstone Graduation Mastery
Demonstrate your engineering expertise to the world.
Mastery Requirements
The capstone requirement is a **full AI product** with all the features taught in the course—autonomous agents, RAG, usage-based billing, and deep observability. Every project is **personally tested by our team** for production-grade reliability and architectural integrity.
Multi-Agent Orchestration
Vector-driven Memory (RAG)
Stripe Token-Billing
Azure/Vercel Auto-Scaling
Observability & Analytics
Production README & Case Study
SXAI-V26-04
Mastery Level 04
Applied AI Engineer
Cohort Enquiry
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