Ten end-to-end AI projects. Each module is a full build with scope, code, eval, and deployment. Hybrid RAG, multi-modal, text-to-SQL, eval gen, semantic cache, doc extraction, orchestration, browser agent, voice, fine-tuning.
The capstone of the Agentic and Applied AI track. Ten modules, each one a deep production-grade project. Each module's 8 challenges are the build steps; the project task is the final submission with all deliverables. Topics span the full breadth of applied AI in 2026: production RAG (hybrid, multi-modal, text-to-SQL), LLM ops (semantic caching, automated eval generation, observability), agents (orchestration, browser, voice), and model customization (LoRA fine-tuning). Each project is self-contained: pick the ones that match your needs and ship them.
Built by Lakshya Kumar
Paste this into any AI chat. Fill in the bracketed parts with your context — you'll get back a straight answer on whether this belongs on your plate.
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Sign in to applyComplete all modules, then submit the required number of capstone projects. Each must earn a passing rating from an admin reviewer.
Pick 3 of the 10 projects that match your current work or career interest. Ship each to production-quality (real users OR realistic eval; documented deliverables per the module rubric). Submit: live links/repos for each, eval results, the 1-page writeup per project.
Ship Modules 1 (Hybrid RAG), 2 (Multi-modal RAG), and 3 (Text-to-SQL) together as a unified knowledge-search platform. All three over the same corpus where applicable. Submit unified demo + eval.
I'm taking "Applied AI Projects" — the capstone course of the Agentic and Applied AI track. 10 modules, each a full production project. Topics: hybrid RAG, multi-modal RAG, text-to-SQL with guardrails, eval generation, semantic caching, document extraction, agent orchestration, browser agents, voice agents, LoRA fine-tuning. My context: 1. My current product / project is: [describe] 2. My current AI experience: [shipped X / built Y / just starting] 3. My team's main pain right now: [hallucinations / cost / latency / safety / scope] 4. My biggest skill gap: [which of the 10 areas] Given that, answer: - Which 3 projects should I prioritize and why? - What's the realistic 4-week plan if I have 10 hours/week? - Name 1 project I should skip and why. - If I had to pick ONE project that would have the biggest impact on my work, which?
Ship Modules 4 (Eval Generation), 5 (Semantic Cache), and a 'monitoring + cost optimization' bundle as one cohesive ops layer on an existing LLM service. Submit code, dashboards, cost-savings report.
Ship Modules 7 (Orchestration), 8 (Browser), 9 (Voice) as a single multi-modal agent platform — text-driven orchestration of browser actions + voice handoff. Submit demo, traces, eval.
Ship Module 6 (Document Extraction) + Module 10 (LoRA Fine-Tuning) as a paired system: extract documents, label the extractions, fine-tune a small model on the labels, serve at lower cost. Submit pipeline + cost-saving analysis.
Module 8's foundation.