- Type Learning
- Level Intermediate
- Time Days
- Cost Paid
ALIP Context Engineering
Issued by
The Swift Group
AI Literacy for Individual Practitioners (ALIP): Context Engineering teaches building the systems (pipelines, retrieval, synthesis, evaluation) that scale AI-assisted work beyond a single context window. This 4-day program (Track 2: 16 blocks, 15 graded labs, 5-deliverable capstone) covers context optimization, RAG pipeline design, provenance-tracked synthesis, evaluation, drift monitoring, and secure, access-controlled systems. Confers the Certified Context Engineering Practitioner designation.
- Type Learning
- Level Intermediate
- Time Days
- Cost Paid
Skills
- Access Control
- Agentic RAG
- Artificial Intelligence (AI)
- BM25
- Chunking Strategies
- Contextual Chunking
- Context Window Optimization
- Cost Estimation
- CRAG (Corrective RAG)
- Cross-Encoder Reranking
- Data Provenance
- Drift Detection
- Golden Test Set
- Graph RAG
- Hybrid Search
- Knowledge Base (KB)
- Knowledge Management
- Multi-Source Synthesis
- Prompt Injection Defense
- Query Processing
- RAGAS
- RAG Pipeline Troubleshooting
- Reciprocal Rank Fusion (RRF)
- Retrieval Augmented Generation (RAG)
- Technical Documentation
- Token Budgeting
- Vector Embeddings
Earning Criteria
-
Complete all 16 blocks and 15 hands-on labs of the 4-day ALIP Context Engineering program (Track 2, Intermediate)
-
Pass at least 11 of 15 graded labs with a score of 70% or higher
-
Complete all five deliverables of the graded capstone project at 70% or higher
-
Achieve a passing score of 700 or higher (1000-point scale) on the proctored adaptive final exam
Standards
ALIP final examinations are developed and audited in accordance with the Standards for Educational and Psychological Testing (AERA/APA/NCME): documented alignment of every exam item to instructed material, reviewed cut scores, and post-administration item analysis.
Every exam item is authored and audited against NBME item-writing guidelines (Haladyna): single defensible keys, plausible distractors, and independent flaw sweeps to remove trick, untaught, or cue-laden items.
ALIP courseware and examinations are built to Section 508 and WCAG 2.1 AA accessibility standards, including semantic markup, screen-reader compatibility, and keyboard navigation.
Retrieval pipeline evaluation is taught and assessed using RAGAS, the open-source RAG evaluation framework: faithfulness, answer relevancy, and context precision/recall metrics, with golden test sets and drift monitoring as the production evaluation baseline.