Enroll Course: https://www.udemy.com/course/learning_transformer/
The course ‘Transformerを詳しく学ぼう！ -PyTorchで実装するAttention、Transformer-‘ on Coursera offers an in-depth exploration of one of the most revolutionary technologies in AI today: the Transformer architecture. Designed for learners who want to understand how Transformers underpin powerful models like GPT-3.5 and GPT-4, this course provides a thorough overview of the mechanics behind these models and guides learners through implementing their own Transformer using PyTorch.
What sets this course apart is its practical approach. Starting with the basics, it covers the foundational concepts such as Attention mechanisms, embeddings, and the overall architecture of Transformers. The instructor makes complex topics accessible, making it suitable for those with a basic understanding of Python and machine learning.
The course is structured into four main sections. The first introduces the Transformer concept and the development environment, ensuring learners are well-prepared. The second dives into the Attention mechanism, explaining how models focus on relevant parts of data. The third discusses input embeddings, crucial for understanding how raw data is transformed into meaningful vectors. The final section is highly practical, where students build their own Transformer from scratch using PyTorch, solidifying their understanding.
One of the highlights is the use of Google Colaboratory, which makes the hands-on implementation seamless and accessible without complex setup. Participants receive a Python basics notebook, easing the learning curve.
Overall, I highly recommend this course for aspiring AI developers, researchers, and enthusiasts eager to grasp the inner workings of Transformers and generateAI. By the end of the course, you’ll have a solid conceptual and practical understanding of Transformers, empowering you to innovate or optimize AI models in your projects.
Enroll Course: https://www.udemy.com/course/learning_transformer/