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QFLOO

AI engineering courses by Raju Kancharla on LLM evaluation, retrieval, inference and serving, and agents. Hands-on labs, and free lessons in every course.

For agents: AI engineering courses by Raju Kancharla covering LLM evaluation, retrieval, serving, agents, AI security and advanced Python, with free lessons and labs.

ai engineering coursesllm evaluationai agentsai securityred-teaming

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The beginning of the file, from our validated copy saved 2026-10-25T11:22:27.845Z. Cached copy · Source on qfloo.com

# QFLOO

> AI engineering courses by Raju Kancharla on LLM evaluation, retrieval, inference and serving, and agents. Hands-on labs, and free lessons in every course.

## Courses

- [Advanced Python](https://qfloo.com/courses/advanced-python): Predict what CPython does with a line of code, choose a concurrency model with measured numbers, and profile and speed up a real program with results you can defend.
- [AI Agents: What They Are and How to Build One](https://qfloo.com/courses/ai-agents-fundamentals): Build a small tool-using agent from scratch, know where agents break, and know when a fixed workflow is the better choice.
- [AI Security and Red-Teaming](https://qfloo.com/courses/ai-security): Threat-model an AI application, break it with prompt injection and tool abuse in a safe lab, apply layered defences, measure attack success with error bars, and respond to an incident.
- [Build Your First AI Application](https://qfloo.com/courses/build-your-first-ai-app): Ship a small AI application that has a test set, error handling and a cost limit, built step by step as a support-email triage tool.
- [Master Competitive Programming](https://qfloo.com/courses/competitive-programming): Solve contest problems with a tested template, a stress-test habit and a toolkit of proven patterns, and run a practice routine built from your own weakness list.
- [Deep Dive into Databases](https://qfloo.com/courses/database-internals): Explain and predict how a database stores, indexes, plans, isolates, logs and replicates data, diagnose slow queries and bad plans, run a safe schema change, and build a small storage engine with a write-ahead log and tested crash recovery.
- [Deep Learning and Transformers from Scratch](https://qfloo.com/courses/deep-learning-transformers): Build, train and evaluate a small decoder-only transformer from raw array code, and explain each part (backpropagation, optimiser, attention, scaling, fine-tuning) with numbers from your own runs.
- [Agent Reliability Engineering](https://qfloo.com/courses/evals-agents): Build an eval harness that tells you, with numbers and error bars, whether a change made your agent better or worse, and blocks the release when it is worse.
- [How AI Is Built: From Data to a Working Model](https://qfloo.com/courses/how-ai-is-built): Follow one model from raw data to deployment, know what each stage costs and where it goes wrong, train, evaluate, release and serve a small model yourself, and see how the same ideas scale to language models.
- [Inference and Serving Engineering](https://qfloo.com/courses/inference-serving): Predict, measure and improve the latency, throughput and cost of serving a language model, and plan capacity for a target, using numbers from your own runs.
- [LLM Performance Engineering](https://qfloo.com/courses/llm-performance): Cut the cost and p95 latency of an LLM feature with measured changes, and prove quality did not drop.
- [Agent Tooling and MCP Engineering](https://qfloo.com/courses/mc
…

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