Explore the ethical implications of AI technology and the importance of responsible AI development and usage.

Learn how to implement the Porter Stemming Algorithm for text processing. Discover how this widely-used algorithm reduces words to their root form for effective natural language processing.

Explore the concept of world models in AI and their applications in simulating and understanding environments.

Build distributed, fast, and scalable models with H2O, an end-to-end ML framework widely used for fraud risk, churn, advertising, and healthcare analytics.

This course covers the strategic implementation of generative AI in business operations.

Learn dynamic programming techniques in Python to optimize algorithms and improve program efficiency, covering key concepts and practical examples.

Learn how to implement easy and accurate speech-to-text systems using Python. Explore libraries and techniques for converting audio into text for real-time transcription applications.

Our future is here and it relies on data. Medical robots, smart homes and cities, predictive policing, artificial intelligences – all are fuelled by data and all promise new benefits to society. But will these innovations benefit everyone? Who stands to gain and who is put at risk? How can we ensure that data is part of a just and sustainable world?

Learn to create AI applications with prompt engineering in this introductory online course. Go beyond AI basics, and learn technical and practical skills to harness the power of this emerging technology. Some experience with JavaScript, Node.js, and APIs is recommended.

This course provides a practical introduction to ChatGPT, from signing up to mastering its advanced features. Topics covered include conversing with ChatGPT, customizing it, using it for productivity and building chatbots, as well as advanced applications like language translation and generating creative content. Best practices and tips for using ChatGPT are also included.

Explore efficient fine-tuning of neural networks using LoRA (Low-Rank Adaptation) and PyTorch. Learn how to apply LoRA for parameter-efficient training of complex models in real-world scenarios.

Explore the concepts of eigenvectors and eigenvalues and their applications in machine learning and data science.