Transformer Models and BERT Model
This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference. This course is estimated to take approximately 45 minutes to complete.
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: LLM Foundations
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
10 Beginner-Friendly AI Data Labeling Jobs Anyone Can Start in 2026
Medium · AI
Why Most Students Are Using ChatGPT Wrong (And the Prompts That Actually Work).
Medium · ChatGPT
We Tested Claude vs ChatGPT on 20 Real Work Tasks: Here’s What Won
Medium · AI
We Tested Claude vs ChatGPT on 20 Real Work Tasks: Here’s What Won
Medium · ChatGPT
🎓
Tutor Explanation
DeepCamp AI