Welcome to the 8^th Summer School on AI
With focus on Computer Vision & Machine Learning

IIIT-H is happy to announce the commencement of the 8^th episode of its Summer School Series, an exciting opportunity for those interested in diving into the fundamentals of Artificial Intelligence. The 8^th summer school will be a research training event with a global scope aiming at equipping participants with the relevant advances in the critical and fast developing area of artificial intelligence.

Artificial Intelligence is poised to become one of the most revolutionary technologies of our time. Every day, we interact with intelligent systems and services in various forms, including apps on our phones, websites, and other devices. Technology never ceases to mimic the human brain and thus AI has gained a lot of interest for decades. AI is the umbrella of several breakthrough fields, machine learning is a subset of AI, wherein computer vision is also the subset of machine learning. The Summer School covers a wide range of topics in Artificial Intelligence from a variety of perspectives. Renowned academics and industry pioneers will lecture and share their views with the audience.

• The curriculum consists of a series of enriching sessions conducted by leading faculty from various disciplines, bringing their diverse experiences to the topic of AI.
• It also includes interactive talks with leading academicians in the field of AI and several experienced industry practitioners from top organizations across the world.
• The program is also designed to create connectivity and networking among participants through peer collaboration, simulation, and engagement.
• Special focus on recent advancements in fields of AI, Computer Vision and Machine Learning.

• The intended audience for the Summer School are those currently enrolled in Masters or PhD programs in the fields of AI, computer vision, and other related areas.
• The program is also open to undergrads who are very enthusiastic about the field.
• And to academics and industry practitioners inclined towards research.
• Note : A basic understanding of the concepts of AI and a mathematical background is expected.