Project

A project proves you can build an end-to-end LLM application, data to model/prompt to evaluation to deployment-ready workflow, not just run demos. It becomes a standout portfolio piece because it shows practical impact: accuracy, reliability, and responsible use of LLMs.

Getting Started

List of Probable Project Topics

  • RAG Chatbot for PDFs/Docs (citations, chunking, embeddings, vector DB)
  • Domain-Specific QA System (healthcare/legal/finance—public data only, with guardrails)
  • Meeting/Interview Summarizer (action items, owners, deadlines; quality scoring)
  • Academic Paper Assistant (paper → structured summary, contributions, limitations, future work)
  • Customer Support Copilot (ticket classification + suggested replies + tone control)
  • Text Classification with LLM + Baselines (compare TF-IDF, BERT, LLM prompting)
  • Information Extraction Pipeline (entities/relations from contracts, resumes, invoices)
  • Text-to-SQL System (natural language → SQL for a given database schema)
  • Personalized Tutor (explain concepts, generate quizzes, adapt difficulty)
  • Multilingual Translator + Style Control (formal/informal; glossary constraints)
  • Bias & Safety Evaluation Suite (toxicity, hallucination, fairness checks; red teaming)
  • Hallucination-Resistant Summarization (fact-checking via retrieval + citation)
  • Content Moderation Assistant (policy-aware labeling + rationale generation)
  • Resume/Job Match Analyzer (skills extraction + gap analysis + tailored bullet rewriting)
  • Semantic Search Engine (hybrid BM25 + embeddings; reranking with a small LLM)
  • Prompt Engineering Cookbook (system prompts, templates, evaluation harness)
  • Fine-tuning/PEFT Mini-Study (LoRA on a small dataset + ablations)
  • Agentic Document Workflow (ingest docs → extract → validate → write report)