Bangalore: Amazon India announced the launch of ML Summer School – an integrated learning experience for students to learn applied Machine Learning (ML) skills, making them industry ready for careers in ML. This program has been introduced to help train students in ML and address the growing demand for talent with this skillset across various industries. The curriculum of ML Summer School will cover the fundamental concepts in ML while linking them to practical industry applications through an immersive 3-day course. Students will get to learn first-hand on how advanced ML techniques such as Deep Learning and Probabilistic Graphical Models can be leveraged to solve specific business problems in the e-commerce domain such as demand forecasting, catalogue quality, product recommendations, search ranking and online advertising.
A batch of students from select tech campuses in India will be presented with the opportunity to engage through virtual classroom tutorials followed by interactive Q&A sessions with scientists at Amazon. For students with prior exposure to certain areas of ML, the program can act as a refresher course, while additionally providing a practical perspective on ML applications in industry. Participants of ML Summer School will be identified through an online assessment. They will also have access to the Amazon Research Days (ARD) conference where they can learn about technology trends in industry through presentations from renowned ML leaders around the world.
Rajeev Rastogi, VP – India Machine Learning at Amazon says, “With the pace of advancements in ML, we are proactively helping students to learn about the latest trends in the field of ML and apply them to solve real-world problems. As a first step in this extensive science talent development journey, we have started with ML Summer School where we have collaborated with universities to provide hands-on learning experiences to students who are passionate to learn more about ML applications in industry. Our aim is to prepare students for science roles – this will help to reduce the gap between the growing demand for ML roles across companies and the talent pool with applied ML skills.”
For enrolment and further details on ML Summer School, please visit https://
