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NLP & LLMs

Master natural language processing from text preprocessing to large language models and transformers. Learn GPT architecture, fine-tuning, and prompt engineering.

30-40 hours total22 modulesCertificate included

Course Modules

1

Introduction to NLP

Language understanding fundamentals

2

Text Preprocessing

Tokenization, stemming, lemmatization

3

Bag of Words & TF-IDF

Classical text representations

4

Word Embeddings

Word2Vec, GloVe, FastText

5

Sequence Models for NLP

RNNs and LSTMs for text

6

Attention Mechanisms

The key to modern NLP

7

Transformer Architecture

Attention is all you need

8

BERT Deep Dive

Bidirectional encoders

9

GPT Architecture

Autoregressive language models

10

Text Classification

Sentiment, topics, intent

11

Named Entity Recognition

Extracting entities from text

12

Question Answering

Building QA systems

13

Text Generation

Creative text with LLMs

14

Summarization

Extractive and abstractive

15

Machine Translation

Neural machine translation

16

Fine-tuning LLMs

Adapting models to tasks

17

Prompt Engineering

Getting the best from LLMs

18

RAG Systems

Retrieval-augmented generation

19

LLM Evaluation

Metrics and benchmarks

20

Responsible AI in NLP

Bias, safety, and ethics

21

Production NLP Systems

Scaling and deployment

22

Capstone: Build a Chatbot

End-to-end NLP project