Be a part of our community of 1M+ users who develop and demonstrate their skills on CodeSignal
4 courses
72 practices
14 hours
Dive deep into the Transformer Architecture! Trace the evolution from RNNs to Transformers by building attention and full Transformer models from scratch, then leverage Hugging Face to fine-tune and deploy state-of-the-art NLP—gaining both core understanding and real-world skills.
You'll explore why RNNs and LSTMs struggle with long sequences, then build attention mechanisms from the ground up, mastering the QKV paradigm and creating reusable attention modules in PyTorch.
Bringing Transformers to Life: Training & Inference
4 lessons
16 practices
You'll combine all Transformer components into a complete model, prepare synthetic datasets, implement autoregressive training with teacher forcing, and explore different decoding strategies for sequence generation.
You'll explore the powerful Hugging Face ecosystem and master different pre-trained Transformer architectures, understanding the specific characteristics of BERT, GPT-2, and T5 models along with their tokenizers and use cases.
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Faith Yim
Software Engineer
+14
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Alex Bush
Full Stack Engineer
+9
I'm really impressed by the AI tutor Cosmo's feedback about my code. It's honestly kind of insane to me that it's so targeted and specific.
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Tech consultant
+8
I tried Leetcode but it was too disorganized. CodeSignal covers all the topics I'm interested in and is way more structured.
Jonathan Miller
Senior Machine Learning Engineer
+12
I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!
