IRL & Online Program
NLP Engineering Professional
Learn transformers, RAG architecture, and fine-tuning models to build enterprise-grade conversational agents.
Hands-on Highlights
- Build a multilingual sentiment analysis API
- Train custom Word2Vec and transformer embeddings
- Develop a semantic search engine using Vector DBs
- Deploy a conversational customer support bot
Detailed Syllabus
Week 1-2
Classical NLP & Embeddings
- Text preprocessing and tokenization
- TF-IDF and Count Vectorizers
- Word2Vec and GloVe embeddings
- Building a baseline sentiment classifier
Week 3-4
The Transformer Revolution
- Self-attention mechanism explained
- Encoder-only (BERT) vs Decoder-only (GPT)
- Fine-tuning BERT for text classification
- Named Entity Recognition (NER)
Week 5-6
Semantic Search & RAG
- Sentence transformers and dense embeddings
- Building a semantic search engine
- Retrieval-Augmented Generation workflows
- Evaluating RAG performance (RAGAS)
Week 7-8
Conversational AI Systems
- Dialogue state tracking
- Integrating LLMs into chatbots
- Handling safety, bias, and guardrails
- Deploying scalable NLP APIs
Target Roles & Career Paths
NLP Engineer
Conversational AI Developer
Search & Relevance Engineer
Machine Learning Engineer
These are the primary roles you will be equipped to apply for upon successful completion of the course and portfolio projects.