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Generative AI Models for Natural Language (NLP & NLU)

Premium
IntermediateCourse

Build job-ready AI models using NLP and earn valuable practical experience and credentials in just three weeks. Knowledge of Python and PyTorch is required.

Language

  • English

Topic

  • Artificial Intelligence

Skills You Will Learn

  • N-Gram, PyTorch Torchtext, Generative AI For NLP, Word2Vec Model, Sequence-to-Sequence Model

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 7 hours

Platform

  • SkillsNetwork

Last Update

  • May 30, 2025
About this Course
This Generative AI Models for Natural Language (NLP & NLU) intermediate-level course teaches you the practical skills you need for data analysis roles.  
 
You will learn: 
 
  • Job-ready skills in 3 weeks, plus you’ll get practical experience employers look for on a resume and an industry-recognized credential 
  • How to use one-hot encoding, bag-of-words, embedding, and embedding bags to convert words to features 
  • To build and use word2vec models for contextual embedding 
  • To build and train a simple language model with a neural network 
  • To use N-gram and sequence-to-sequence models for document classification, text analysis, and sequence transformation 
 
Course overview 
 
Organizations are implementing generative AI models to enhance productivity and overall operations.  
 
This IBM course will teach you how to implement, train, and evaluate Generative AI models for Natural Language Processing (NLP). The course will help you acquire knowledge of NLP applications, including document classification, language modeling, language translation, and fundamentals for building small and large language models. 
 
You will learn about converting words to features. You will understand one-hot encoding, bag-of-words, embedding, and embedding bags. You’ll also learn how Word2Vec embedding models are used for feature representation in text data. You will implement these capabilities using PyTorch. 
 
The course will teach you how to build, train, and optimize neural networks for document categorization. In addition, you will learn about the N-gram language model and sequence-to-sequence models. This course will help you evaluate the quality of generated text using metrics, such as BLEU. 
 
You will also practice what you learn using hands-on labs and perform tasks such as implementing document classification using torchtext in PyTorch. You will gain the skills to build and train a simple language model with a neural network to generate text and integrate pre-trained embedding models, such as word2vec, for text analysis and classification. In addition, you will apply your new skills to develop sequence-to-sequence models in PyTorch and perform tasks such as language translation. 
 
Overall, this Generative AI Models for Natural Language (NLP & NLU) course gives you a valuable introduction to Generative AI models and can propel you to ongoing career success. 


Course Syllabus

Module 0: Welcome

·         Video: Course Introduction
·         Reading: Specialization Overview
·         Helpful Tips for Course Completion
·         Reading: Learning Objectives and Syllabus
·         Reading: Grading Scheme
·         Reading: General Information

Module 1: Fundamentals of Language Understanding

·         Reading: Module Introduction and Learning Objectives
·         Video: Converting Words to Features
·         Video: Document Categorization Prediction with Torchtext
·         Video: Document Categorization Training with Torchtext
·         Video: Training the Model in PyTorch
·         Lab: Classifying Documents
·         Video: Language Modeling with N-Grams
·         Video: N-Grams as Neural Networks with PyTorch
·         Lab: Building and Training a Simple Language Model with a Neural Network
·         Summary: Module 1: Fundamentals of Language Understanding
·         Practice Quiz: Fundamentals of Language Understanding
·         Graded Quiz: Fundamentals of Language Understanding

Module 2: Word2Vec and Sequence-to-Sequence Models

·         Reading: Module Introduction and Learning Objectives
·         Video: Word2Vec: Introduction and CBOW Models
·         Video: Word2Vec: Skip-Gram and Pretrained Models
·         Video: Introduction to Sequence-to-Sequence Models and Recurrent Neural Networks
·         Video: Encoder-Decoder RNN Models: Training and Inference
·         Video: Encoder-Decoder RNN Models: Translation
·         Video: Metrics for Evaluating the Quality of Generated Text
·         Reading: Evaluation Metrics for NLP Models
·         Lab: Integrating Word2Vec
·         Lab: Developing a Sequence-to-Sequence Model
·         Reading: Summary and Highlights
·         Practice Quiz: Word2Vec, Sequence-to-Sequence Models
·         Graded Quiz: Word2Vec and Sequence-to-Sequence Models
·         Module 3: Course Cheat Sheet, Glossary, and Wrap-up
·         Reading: Module Introduction and Learning Objectives
·         Reading: Cheat Sheet: AI Models for NLP and Language Understanding
·         Reading: Course Glossary: AI Models for NLP and Language Understanding

Course Wrap-Up

·         Reading: Course Conclusion
·         Reading: Congratulations and Next Steps
·         Reading: Team and Acknowledgements
·         Reading: Copyrights and Trademarks


Recommended Skills Prior to Taking this Course

You should be familiar with Python and PyTorch and have basic knowledge of machine learning and neural network concepts. 
 
To transition to a career in Generative AI models, we recommend you enroll in the full Professional Certificate program and work through the courses in order. Within a few months, you’ll have job-ready skills and practical experience on your resume that will catch an employer's eye! 

Instructors

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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IBM Skills Network

IBM Skills Network Team

At IBM Skills Network, we know how crucial it is for businesses, professionals, and students to build hands-on, job-ready skills quickly to stay competitive. Our courses are designed by experts who work at the forefront of technological innovation. With years of experience in fields like AI, software development, cybersecurity, data science, business management, and more, our instructors bring real-world insights and practical, hands-on learning to every module. Whether you're upskilling yourself or your team, we will equip you with the practical experience and future focused technical and business knowledge you need to succeed in today’s ever-evolving world.

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