Join our session on “Prompt Engineering Essentials: How to Get the Best from AI” to understand how effective prompting techniques can significantly enhance AI-powered outcomes. Learn how to craft high-quality prompts, control AI behavior, and generate more accurate, relevant, and creative responses. Whether you’re new to prompting or looking to refine your skills, this session will offer practical insights to help you get the very best from today’s leading AI systems.

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Agenda for the session

  • Learn to communicate effectively with AI and avoid common prompt errors.
  • Apply techniques to get accurate and impactful results from AI tools.
  • AI and Data Science program
  • Live Q&A

About Speakers

Mr. Matthew Nickens

Senior Manager, Data Science at CarMax

Matthew Nickens is a seasoned data science leader and Senior Manager of Data Science at CarMax, with prior experience at Meta, The Walt Disney Studios, and Twentieth Century Fox. He brings strong expertise in applying AI and analytics to real-world business problems, with a focus on translating complex models into practical solutions. His experience with generative AI and applied analytics positions him well to help professionals master prompt engineering and effectively get the best outcomes from AI tools.

AI and Data Science: Leveraging Responsible AI, Data and Statistics for Practical Impact

The AI and Data Science: Leveraging Responsible AI, Data and Statistics for Practical Impact Program has a curriculum carefully crafted by MIT faculty to provide you with the skills & knowledge to apply data science techniques to help you make data-driven decisions. This data science program has been designed for the needs of data professionals looking to grow their careers and enhance their data science skills to solve complex business problems. In a relatively short period of time, the program aims to build your understanding of most industry-relevant technologies today such as machine learning, deep learning, network analytics, recommendation systems, graph neural networks, and time series.

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