Build on your existing knowledge with intermediate ai ethics techniques and real-world applications.
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
IntermediateTransformer Neural Networks - EXPLAINED! (Attention is all you need)
IntermediateLearn Machine Learning Like a GENIUS and Not Waste Time
IntermediateAll Machine Learning algorithms explained in 17 min
IntermediateAI Ethics, Responsible Use, and Creativity
IntermediateAI Workflow: Feature Engineering and Bias Detection
AdvancedTesting Machine Learning Systems
IntermediateCausal Diagrams: Draw Your Assumptions Before Your Conclusions
IntermediateMLOps with Weights & Biases
IntermediateEthics in AI
IntermediateResponsible AI in Medical Imaging: An Interdisciplinary Educational Initiative
IntermediateBut what is a neural network? | Deep learning chapter 1
IntermediateThe Essential Main Ideas of Neural Networks
IntermediateTransformer Neural Networks - EXPLAINED! (Attention is all you need)
IntermediateLearn Machine Learning Like a GENIUS and Not Waste Time
IntermediateAll Machine Learning algorithms explained in 17 min
IntermediateAI Ethics, Responsible Use, and Creativity
IntermediateAI Workflow: Feature Engineering and Bias Detection
AdvancedTesting Machine Learning Systems
IntermediateCausal Diagrams: Draw Your Assumptions Before Your Conclusions
IntermediateMLOps with Weights & Biases
IntermediateEthics in AI
IntermediateResponsible AI in Medical Imaging: An Interdisciplinary Educational Initiative
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
Transformer Neural Networks - EXPLAINED! (Attention is all you need)
Learn Machine Learning Like a GENIUS and Not Waste Time
All Machine Learning algorithms explained in 17 min
This course explores the ethics and responsible use of generative AI tools. Learners will engage with these tools with a focus on intentionality, sustainability, and responsibility, and learn to evaluate them using the SIFT process.
An advanced course by IBM that covers feature engineering, data ethics, unsupervised learning, and dimensionality reduction. Students will learn about responsible AI, text mining, and data wrangling.
This course covers the best practices for testing machine learning systems. You'll learn how to design and implement tests for data, models, and infrastructure. The course also covers topics such as fairness, privacy, and security in the context of ML testing.
A Harvard University course that teaches the use of causal diagrams (DA Gs) to represent assumptions, understand biases, and guide data analysis for causal inference.
An educational initiative funded by the EPSRC Impact Acceleration Account at Aston University. The project aims to foster an interdisciplinary approach to responsible AI in medical imaging.
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