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G04 Stage C · Applied GenAI 44 h (16 T / 28 P)

LLM Evaluation, Observability & Cost

Proves whether an AI system is good enough to ship, with evidence.

Prerequisite
G02
Modules
6
NOS
SSC/N8121
Statutory mapping

Tech stack

RAGASDeepEvalLangSmithMLflow

Modules

6 modules · 44 hours

M1 · Evaluation strategy

8 h
TOPICS
  • What to measure
  • Offline versus online
  • Golden datasets
  • Dataset curation and maintenance
  • Annotation guidelines
  • Inter-annotator agreement
  • Test-set contamination

Lab: Construct a governed golden dataset with an annotation guide

Course material for this module is in production.

M2 · Retrieval metrics

8 h
TOPICS
  • recall@k
  • precision@k
  • MRR
  • NDCG
  • Hit rate
  • Context precision and recall
  • Evaluating retrieval independently of generation

Lab: Retrieval-only evaluation harness with dashboards

Course material for this module is in production.

M3 · Generation metrics

10 h
TOPICS
  • Faithfulness and groundedness
  • Answer relevance
  • Correctness and completeness
  • Toxicity and safety
  • Deterministic assertions
  • LLM-as-a-judge design
  • Judge bias and calibration
  • Human agreement

Lab: Build and calibrate a judge against human labels

Course material for this module is in production.

M4 · Agent and multi-turn evaluation

6 h
TOPICS
  • Trajectory evaluation
  • Tool-call correctness
  • Task completion
  • Conversation quality
  • Regression suites

Lab: Trajectory evaluation for the G03 agent

Course material for this module is in production.

M5 · Observability

6 h
TOPICS
  • Tracing and spans
  • Prompt and version logging
  • Latency and token dashboards
  • Error taxonomies
  • Sampling live traffic
  • User feedback capture
  • Drift detection

Lab: Instrument a live pipeline with end-to-end tracing

Course material for this module is in production.

M6 · Cost and performance engineering

6 h
TOPICS
  • Token accounting
  • Prompt compression
  • Exact and semantic caching
  • Model routing and tiering
  • Batching
  • Streaming
  • Budget alarms
  • Unit economics per request

Lab: Halve cost per query at constant measured quality

Course material for this module is in production.

Real-world work scenario

Leadership asks whether a prompt change may ship. Run the regression suite, separate retrieval from generation effects, quantify quality delta with confidence, report cost and latency impact, and issue a go/no-go recommendation with evidence.

Assessment

Evaluation harness · calibrated judge · cost-reduction practical