Learn about deep reinforcement learning algorithms and their applications in decision-making and control problems.

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

Dive into the dangerous world of AI phishing and learn how to protect yourself from attacks and misinformation.

Learn about the elements of AI, machine learning and computer vision. Discover the open-source AI tools, and hidden AI gems. Learn how to play with architectural design data using freely available AI model.

Learn about the implementation and practical aspects of Artificial Intelligence and how to write a plan for applying AI in your own organization in a step-by-step manner.

Learn about the implementation and practical aspects of Artificial Intelligence and how to write a plan for applying AI in your own organization in a step-by-step manner.

Learn about the implementation and practical aspects of Artificial Intelligence and how to write a plan for applying AI in your own organization in a step-by-step manner.

Learn to recognize and understand the implications of Artificial Intelligence for organizations, and the importance of compliance and ethics when AI is applied in practice.

Good data is central to effective AI applications. This course teaches the basics of data for AI, covering what data is needed, how to extract data from existing databases and basic data skills including setup of a Python notebook environment, basic data exploration and simple data visualizations.

A one-stop shop to get started on the key considerations about data for AI! Learn how crowdsourcing offers a viable means to leverage human intelligence at scale for data creation, enrichment and interpretation, demonstrating a great potential to improve both the performance of AI systems and their trustworthiness and increase the adoption of AI in general.

In today's data driven world, a lot of the data isn't text anymore. This course will teach you how to recognize and classify images using neural networks.

Managing the machine learning process using recommended practices is a must to enable collaboration, tracing, and real-time monitoring. This course will teach you what are the main concerns and issues you need to consider while developing a machine learning model and after deploying it.