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    Software Trainings · Prompt Engineering track

    Prompt engineering treated as software, not folklore.

    Track · Generative AI Engineering with PythonDuration · 12 weeksLevel · Intermediate — AdvancedFormat · Live cohort · Online

    A six-week track that turns prompting into engineering: system design, structured output with schemas and tools, evaluation harnesses with golden sets and LLM-as-judge, plus the safety, cost, and latency guardrails production calls actually need.

    What this track delivers

    Why this track is different.

    1. 01

      System-prompt design

      Role design, decomposition, few-shot, and the patterns that hold up beyond demos.

    2. 02

      Structured output

      JSON schema, function/tool calling, parsing-and-repair pipelines across GPT, Claude, and Gemini.

    3. 03

      Evaluation harness

      Golden sets, regression suites, drift detection — the part most teams skip and then regret.

    4. 04

      Production guardrails

      Jailbreak defense, PII handling, cost & latency budgets — baked into every call, not bolted on later.

    Week-by-week

    Syllabus in order.

    1. Week 1–2
      LLM foundations

      Transformer intuition, API patterns, prompt engineering.

    2. Week 3–4
      RAG pipelines

      Embeddings, vector stores, chunking, retrieval quality.

    3. Week 5–6
      Tool use & agents

      Function calling, agent loops, memory, multi-step reasoning.

    4. Week 7–8
      Evaluation & safety

      Eval harnesses, red-teaming, guardrails, PII handling.

    5. Week 9–10
      Production systems

      Streaming, caching, cost control, observability, deployment.

    6. Week 11–12
      Capstone

      Design, build, evaluate, and ship a production AI application.