Build on your existing knowledge with intermediate fairness techniques and real-world applications.
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Depends on the specific domain
Comfortable coding and debugging
But what is a neural network? | Deep learning chapter 1
IntermediateThe Essential Main Ideas of Neural Networks
IntermediateTransformers Explained - How transformers work
IntermediateHow AI Image Generators Work (Stable Diffusion / Dall-E) - Computerphile
IntermediateTransformer Neural Networks - EXPLAINED! (Attention is all you need)
IntermediateIllustrated Guide to Transformers Neural Network: A step by step explanation
IntermediateLearn Machine Learning Like a GENIUS and Not Waste Time
IntermediateAll Machine Learning algorithms explained in 17 min
IntermediateNatural Language Processing: Crash Course AI #7
IntermediateBut what is a neural network? | Deep learning chapter 1
IntermediateThe Essential Main Ideas of Neural Networks
IntermediateTransformers Explained - How transformers work
IntermediateHow AI Image Generators Work (Stable Diffusion / Dall-E) - Computerphile
IntermediateTransformer Neural Networks - EXPLAINED! (Attention is all you need)
IntermediateIllustrated Guide to Transformers Neural Network: A step by step explanation
IntermediateLearn Machine Learning Like a GENIUS and Not Waste Time
IntermediateAll Machine Learning algorithms explained in 17 min
IntermediateNatural Language Processing: Crash Course AI #7
IntermediateFollow these courses in order to complete the learning path. Click on any course to enroll.
But what is a neural network? | Deep learning chapter 1
The Essential Main Ideas of Neural Networks
Transformers Explained - How transformers work
How AI Image Generators Work (Stable Diffusion / Dall-E) - Computerphile
Transformer Neural Networks - EXPLAINED! (Attention is all you need)
Illustrated Guide to Transformers Neural Network: A step by step explanation
Learn Machine Learning Like a GENIUS and Not Waste Time
All Machine Learning algorithms explained in 17 min
Natural Language Processing: Crash Course AI 7
Explore related content to expand your skills beyond this learning path.
Build on your existing knowledge with intermediate fairness techniques and real-world applications.
You'll work through Deepen your understanding with advanced concepts; Build more complex real-world projects; Learn optimization and best practices; Identify and mitigate bias in AI systems; Apply fairness metrics to evaluate models; Design AI systems with transparency in mind.
About 2 hours of study across 9 courses — and you can go at your own pace.
It's pitched at intermediate level, so a little prior familiarity helps.
9 curated courses, sequenced from foundational to advanced.
The courses in this path can be started for free.
Enroll in this path to track your progress and stay motivated.