Coding a ChatGPT-style Language Model Scratch in PyTorch from

  • AdvancedLevel

  • 1 hrs 0 minsDuration

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About this Course

  • Hands-on Model Building: Learn to code a ChatGPT-style language model from scratch using PyTorch, understanding every component step by step.
  • NLP with PyTorch: Master natural language processing concepts like tokenization, embeddings, and attention mechanisms through practical coding exercises.
  • Model Training & Tuning: Train, fine-tune, and evaluate your language model, exploring techniques to improve accuracy and handle complex language tasks.

Learning Outcomes

Build GPT Models

Create a language model from scratch with PyTorch.

Understand NLP Basics

Master tokenization, embeddings, and attention layers.

Train & Fine-Tune Models

Training and optimizing models for better performance.

Deploy Language Models

Learn to test and deploy your custom language models.

Who Should Enroll

  • Aspiring NLP Engineers: Learn to build and train language models from scratch using PyTorch and GPT concepts.
  • Data Science Enthusiasts: Explore the inner workings of ChatGPT-like models and gain hands-on coding experience.
  • AI/ML Developers: Enhance your skills by understanding and implementing transformer-based architectures step by step.

Get this Course Now

With this course you’ll get

  • 300 hour

    Duration

  • Dr. Joshua Starmer

    Instructor

  • Advanced

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Globally recognized certificate
  • Verifiable online credential
  • Enhances professional credibility

Frequently Asked Questions

Looking for answers to other questions?

Basic knowledge of Python and machine learning fundamentals is recommended. Familiarity with PyTorch is helpful but not mandatory, as the course includes step-by-step guidance.

The course features video tutorials, hands-on coding exercises, and downloadable resources, allowing you to learn at your own pace.

Yes! The course walks you through the entire process, from data preparation to implementing and training a decoder-only transformer.

You can start by doing the tests at the end of each lesson. In addition, you can apply Natural Language Processing to solve the following Practice Problems at Datahack:

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