E2E Testing ChatBot, AI Agent, RAG, MCP Server with DeepEval Framework
Test and evaluate LLM apps, chatbots, AI agents, RAG pipelines, and MCP servers with DeepEval.
🔒 Secure checkout♾️ Lifetime access📓 Written notes + diagrams💻 Full GitHub project🎥 Class recordings
3
hands-on projects
29
metrics you will run
4
systems: chatbot · RAG · agent · MCP
25
pytest files
Highly Recommended Course. Easy to Understand, Informative, Very Well Organized.Thank you!!
John Smith
This is an amazing course!. Very well thought out Course offering lots of value. Thanks!
Emma Wells
order details
What is included in your enrolment
| Included | Detail |
|---|---|
| Lesson 1 — DeepEval foundations | 19 illustrated sections: what LLM-as-judge is, installation with the correct version pin, judge selection across OpenAI / Groq / Ollama, the LLMTestCase primitive, goldens, and the complete 29-row metric architecture |
| Lesson 2 — the hands-on project | Three build-along projects plus a bonus: a real support chatbot, a full RAG pipeline, a live black-box vendor bot, and synthetic summarization |
| Agents & MCP servers | The five-step recipe for adding any new target, with task-success, tool-choice and argument-correctness rubrics |
| The complete GitHub project | All three subsystems, the metric registry, 41 goldens, the FastAPI dashboard and all 25 pytest files |
| CI workflow | A GitHub Actions pipeline with marker-sliced fast gates and a nightly full sweep |
| Reusable skill playbook | A single file that regenerates this whole architecture for your own product |
| Class recordings | Added to the curriculum, alongside the written notes |
| Access | Lifetime — including future updates to these lessons |
the payoff
What you can do the week after
Score an AI release
Replace "it feels worse this week" with a score, a threshold and a red build.
Localise the defect
Say whether the retriever or the generator caused a wrong answer — the single most useful thing a QA can tell an AI team.
Gate a pull request
A marker-sliced eval suite that runs in CI and blocks a bad prompt change.
Sign off a vendor bot
Grade a third-party chatbot you have no access to, including leakage probes.
Cover agents and MCP
Extend the same harness to tool-calling systems without rewriting anything.
Show your working
A dashboard with live scores, judge reasons and run history for the release meeting.
before you buy
Honest expectations
| Question | Straight answer |
|---|---|
| Do I need an API key? | No. Local Ollama judges for free, and the apps under test fall back to mock mode. A key just makes runs faster and scores steadier. |
| Do I need LLM experience? | None. Prompts, embeddings, RAG and LLM-as-judge are built from zero. |
| What do I need? | Python you can read and write, pytest basics, and comfort with curl and JSON. |
| Is this vendor lock-in to DeepEval? | The metrics are DeepEval; the architecture is framework-agnostic and survives a library swap. |
| Are LLM scores reliable enough to gate a build? | Yes if used correctly — small low-temperature judge, thresholds with headroom, trends over single numbers. We cover the limits honestly. |
| Will this cost me a fortune in API calls? | No. Develop against two or three goldens on gpt-4o-mini, keep the full sweep nightly, or run entirely offline on Ollama. |
💡 Right after payment
You land on a thank-you page with your next three steps, then the course access page with both written lessons ready to read. Nothing to wait for.
Need help before you enrol?
Use the Support link in the menu above. If you are on a company card and need an invoice or a GST number on it, ask before you pay — it is much easier than afterwards.
