Artificial Intelligence is transforming the way businesses use their data to understand consumers and deliver smart solutions. Ecommerce is an industry where data-driven decisions play a crucial part, and deep learning is a prevailing technique used to deliver seamless experiences, such as mapping the right products to relevant consumers.
Join us in an interactive session with Bhaskarjit Sarmah, Data Scientist, Black Rock, as he discusses how deep learning is used in one of the important aspects of an ecommerce business, product cataloging. He also discusses how organizations can leverage no-code tools and implement deep learning in their applications without having to write a single line of code with the No-Code AI and Machine Learning program.
Agenda for the session
- Role of deep learning in product cataloging on e-commerce platforms
- How to make the best use of AI and ML without writing a single line of code
- No Code AI and ML: Building data science solutions program experience
- Q&A session
About Speakers
Bhaskarjit Samah Sarmah
Data Scientist, Black Rock
Shannon is a leadership professional with over 20 years of experience in solution design, data science, strategy, and decision-making. He is currently the Co-founder, CTO, and Head of Data Science at Calido, a product collaboration firm from Silicon Valley, CA. Previously, he was the Director of Data Science at the University of North Carolina at Charlotte and Assistant Professor at Purdue University.
No Code AI and Machine Learning Program by MIT Professional Education
Artificial Intelligence and Data Science are now a force to reckon with. AI will boost global GDP to $15.7 trillion by 2030, according to PwC. This makes professionals with AI skills highly valuable to organizations across industries. In order to help you unlock the power of AI in business, MIT Professional Education offers the No Code AI and Machine Learning: Building Data Science Solutions Program.
In this 12-week program, you will be able to decode the AI landscape by learning the theory and practical applications of supervised and unsupervised learning, time-series analysis, neural networks, recommendation engines, regression, computer vision, and more. With the no-code approach, you will learn to leverage the power of AI and Data Science without having to write a line of code.
