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Model Engineering Track

Fine-Tuning, Alignment and Model Adaptation

Diagnose when weights should change, then engineer governed data, SFT, LoRA and QLoRA, preference optimization, distillation, evaluation, adapter serving, and incident-ready operations.

Advanced · model adaptation
About 275 min reading
47 authored sections

Before you start: Python, tensors, gradient descent, train/validation splits, and LLM fundamentals.

Plan for 8–12 hours of hands-on work in addition to reading. This is an initial estimate; setup and extensions vary.

Open before purchase

A useful preview, not a teaser

Read these complete sections to judge the technical depth, teaching style, and architecture standard before buying.

Preview 1

Course Contract: Earn the Right to Change the Weights

Fine-tuning is a product intervention, not a badge of technical maturity.

Preview 2

Model Adaptation Is a Stack of Interventions

Not every product requirement belongs inside model weights.

Preview 3

Write Examples That Teach the Intended Decision

The model learns correlations in demonstrations, including accidental ones.

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Complete curriculum

47 sections · 5 parts + adaptation studio

Course orientation

  1. Course ContractFree

Part 1 · Choose the Intervention

  1. Adaptation Mental ModelFree
  2. Diagnose the ErrorCourse Pass
  3. Intervention LadderCourse Pass
  4. Choose the Base ModelCourse Pass
  5. Tokenizer and ContextCourse Pass
  6. Objective MapCourse Pass
  7. Experiment ContractCourse Pass
  8. Lifecycle ArchitectureCourse Pass

Part 2 · Engineer Data and Training

  1. Dataset ContractCourse Pass
  2. Rights and PrivacyCourse Pass
  3. Example DesignFree
  4. Dedup and ContaminationCourse Pass
  5. Train and Eval SplitsCourse Pass
  6. Balance and CurriculumCourse Pass
  7. Supervised Fine-TuningCourse Pass
  8. Full Fine-TuningCourse Pass
  9. LoRACourse Pass
  10. PEFT DesignCourse Pass
  11. QLoRACourse Pass
  12. HyperparametersCourse Pass
  13. Packing and MaskingCourse Pass
  14. Distributed TrainingCourse Pass

Part 3 · Align and Compress

  1. Preference DataCourse Pass
  2. RLHFCourse Pass
  3. DPOCourse Pass
  4. RLAIF and PrinciplesCourse Pass
  5. DistillationCourse Pass
  6. Forgetting and DriftCourse Pass
  7. Safety and AlignmentCourse Pass

Part 4 · Evaluate and Operate

  1. Evaluation StrategyCourse Pass
  2. Data Quality DiagnosticsCourse Pass
  3. Model ComparisonCourse Pass
  4. Adapter RegistryCourse Pass
  5. Serving AdaptersCourse Pass
  6. Observability and DriftCourse Pass
  7. Security and GovernanceCourse Pass
  8. Incident ResponseCourse Pass

Part 5 · Architect the Program

  1. Worked CaseCourse Pass
  2. CapstoneCourse Pass

Adaptation Studio

  1. Decision LabCourse Pass
  2. Capacity LabCourse Pass
  3. Release Gate LabCourse Pass
  4. Challenge · Leakage GroupsCourse Pass
  5. AssessmentCourse Pass
  6. Interview QuestionsCourse Pass
  7. ReferencesCourse Pass