Course curriculum

  • 1
    Introduction to NLP
    • Course Introduction
    • Course Handouts
    • What is NLP
    • Common tasks in a NLP Project
    • NLP Libraries
    • Methods of Text Preprocessing - Part 1
    • Methods of Text Preprocessing - Part 2
    • Methods of Text Preprocessing - Part 3
    • Quiz
  • 2
    Building a basic classification model
    • Introduction to dataset and problem statement
    • Hands on Creating a Basic Review Classification Model
    • Understanding TF-IDF and its implementations
    • Understanding N-grams
    • Methods of Preprocessing
    • Hands on Building an basic ANN model
    • Limitations of ANN
    • Quiz
  • 3
    NLP: Recurrent Neural Network
    • Understanding RNN
    • Reading - Understanding the Math within RNN
    • Backward Propagation in RNN
    • Types of RNN
    • Hands on Building an RNN Model with Word Indexing
    • Word Embeddings
    • Hands on Building an RNN Model with Word Embedding
    • Advanced RNN Architectures
    • Hands on Advanced RNN Structures
    • Understanding GRUs
    • Hands on BI-directional GRU model
    • Understanding Long Short Term Memory Network
    • Hands on BI-directional LSTM model
    • Quiz
  • 4
    Attention mechanism and Transformers
    • Introduction to Seq2Seq Models
    • Working of Encoder Decoder in Training and Testing Phase
    • Introduction to Problem Statement
    • Hands on Encoder Decoder Sequence-to-Sequence Model
    • Understanding BLUE, ROUGE and METEOR metric
    • Attention Mechanism
    • Hands on Encoder Decoder Attention Model
    • Introduction to Transformers
    • Flow of information in Transformers
    • Introduction to Google Colab
    • Quiz
  • 5
    Preparing for LLMs
    • Origin of Transformers
    • Pre trained transformers BERT
    • Hands on: Understanding Fine Tuning pretrained Model
    • Hands on: Headline extraction using T5 pretrained Transformer Model
    • BERT vs GPT
    • Quiz

Introduction to Natural Language Processing using PyTorch

This course will help you gain a deep understanding of Natural Language Processing. After this course, you can build advanced NLP Models using the PyTorch framework. With a carefully curated list of resources and exercises, this course is your guide to becoming an NLP expert. By the end of the course, you will have mastered techniques like bag-of-words, RNN, and Transformers.


Who Should Enroll:

  • Professionals: Individuals looking to expand their skill set and apply NLP across different industries.

  • Aspiring Students: For those setting out on their journey to mastering text data analysis and making a mark in the tech world.

Key Takeaways from the course

  • Learn NLP techniques and build real-world NLP Models.

  • Hands-On Experience: Engage with exercises designed to reinforce your learning and apply concepts in real-world scenarios.

What do I need to start the course

  • A working laptop/desktop and an internet connection

  • Large space in your laptop to download necessary files

  • Knowledge of ML, DL, and PyTorch