Discover how Large Language Models (LLMs) are transforming NLP tasks such as summarization, content creation, data extraction, and question answering. This session will explore practical use cases and demonstrate how organizations are leveraging LLMs to automate workflows, improve productivity, and unlock insights from unstructured data.You'll also gain an understanding of how LLMs process language, generate context-aware responses, and can be applied across a variety of business and operational use cases.
Agenda for the session
- How GenAI and LLMs enable summarization, data extraction & content creation
- Understanding LLM capabilities & prompt techniques for accurate results
- AI and Data Science program
- Live Q&A
About Speakers
Mr. Tasleem Ahmad Muzaffar
Senior Data Scientist at CubeSmart
Tasleem Ahmad Muzaffar is a data and AI strategist with expertise in machine learning, analytics, and applied AI solutions. He specializes in helping organizations leverage advanced AI technologies to solve real-world business challenges and extract value from data. With strong experience in NLP and Generative AI, Tasleem focuses on applying LLMs to tasks such as summarization, content creation, data extraction, and question answering.
AI and Data Science: Leveraging Responsible AI, Data and Statistics for Practical Impact Program
The AI and Data Science: Leveraging Responsible AI, Data and Statistics for Practical Impact program from MIT IDSS is designed to help professionals build practical expertise in AI and data-driven decision-making.
Through a curriculum developed by MIT faculty, learners gain a strong foundation in Data Science, Machine Learning, Generative AI, Agentic AI, Deep Learning, and Responsible AI, while developing the technical intuition and strategic judgment needed to apply these technologies to real-world business challenges and drive measurable impact
