Skills you can prove

Evidence from modules, practice, and projects

Competence is shown with artifacts: working chat, cited RAG, traces, and a production checklist — the same evidence used in junior GenAI interviews.

Learning Sections

Completed & verified

Knowledge Checks

Passed diagnostic checks

Modules Completed

0/20

0% of curriculum

Challenges Solved

Build & debug evidence

VERIFIED COMPETENCIES

Skills & Supporting Evidence

Python for AI

In progress

Verification Evidence:

Module 01: functions, JSON, venv, pip

Practice: CLI that filters JSON and writes a report

LLM APIs & prompts

Available

Verification Evidence:

Modules 03–04: streaming chat and JSON templates

Gate A: working API chat + validated JSON output

RAG systems

Locked until Module 07

Verification Evidence:

Modules 06–09: embeddings, RAG, hybrid search, LangChain

Gate B: citations plus a 15-question eval sheet

Agents & production

Locked until Module 10

Verification Evidence:

Modules 10–13 and 17: tools, graphs, guardrails, cost

Gate C: bounded agent with traces

ACADEMIC REMEDIATION

AI analysis of your code challenge submissions highlights specific concepts that require review before advancing.

Grounded RAG answers

Practice citations, abstention, and a 15-question faithfulness eval.

Bounded tool-using agents

Add max steps, traces, and confirmation before side effects.

Production guardrails

Cover secrets, prompt-injection resistance, tracing, and cost caps.