Duration: 6 Sessions (2 Sessions Per week)
Contact Hours: 18
Start Date: 24th July
Time: 5:30 to 8:30 PM
Session Dates: 24th, 27th, 31st July and 3rd, 8th August, 10th August

Course overview:
This course will provide a broad introduction to latest developments in the field of Explainable Artificial Intelligence and its application in various research domains. As our reliance on AI models is increasing day by day, it’s also becoming equally important to explain how and why AI is making a particular decision. Recent laws have also caused the urgency about explaining and defending the decisions made by AI systems.
In this seminar, you will learn about tools and techniques using Python to visualize, explain, and build trustworthy AI systems. We will discuss all-important XAI techniques like LIME, SHAP, DiCE, LRP, Contrastive and Counterfactual Explanations Method. You will be introduced to several open-source explainable AI tools for Python that can be used throughout the machine learning project lifecycle.

Who is the course for?
• Beginner Python programmers who already have some foundational knowledge with machine learning libraries.
• Data scientists and Researchers who already use Python for building AI models and can benefit from learning the latest explainable AI open-source toolkits and techniques.