Intermediate · Short courseOnline · live classesOn campus
NLP & Large Language Models
Teach machines to read and write — classic NLP through modern LLMs, embeddings, RAG and fine-tuning.
Enroll nowApproved & recognised by the University of Mysore
Level
Intermediate
Duration
10 weeks
Time commitment
7–9 hrs/week
Format
Live online or on campus
About this course
Natural language processing is where AI meets the real world of text: search, chatbots, document analysis, translation. This course covers the classical foundations quickly, then goes deep on the modern stack — embeddings, vector search, retrieval-augmented generation, and fine-tuning open-source LLMs. You finish by building a working AI assistant over your own documents.
Who it's for: Python-comfortable learners who want to build products on top of language models.
What you'll learn
Process and represent text: tokenisation, embeddings, vector spaces
Build search and classification over real document sets
Design RAG systems: chunking, retrieval, grounded answers
Fine-tune open-source LLMs for specific tasks
Evaluate language systems beyond "it looks right"
Syllabus
Text fundamentals
Weeks 1–2- Tokenisation and preprocessing
- Classic NLP tasks
- Word and sentence embeddings
The LLM stack
Weeks 3–5- How LLMs are trained
- Prompting vs fine-tuning
- Vector databases and semantic search
RAG & fine-tuning
Weeks 6–8- Retrieval-augmented generation
- Fine-tuning open models
- Evaluation and guardrails
Capstone
Weeks 9–10- Build an assistant over real documents
- Measure quality honestly
- Demo day
Tools you'll use
Hugging FaceLangChainChromaDBOpenAI / Claude APIsspaCy
Certificate
Finish the course and its capstone project to earn a FuturAIse Academy Certificate of Completion — verifiable online, with the projects to back it up.