Join our session on “Prompt Engineering Essentials – How to Get the Best from AI” to learn how the quality of prompts directly impacts the outputs generated by AI models. Discover how to structure clear, effective prompts to guide AI systems toward accurate, relevant, and actionable responses. This session will cover practical prompt frameworks, common pitfalls, and real-world examples to help you interact more effectively with AI tools. Whether you’re new to AI or looking to refine your approach, this session will equip you with essential techniques to get the most value from AI.
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.
- No Code AI and Machine Learning program
- Live Q&A
About Speakers
Mr. Matthew Nickens
Senior Manager, Data Science at CarMax
Matthew Nickens is a seasoned data-science leader currently serving as Senior Manager of Data Science at CarMax. With prior roles at Meta, The Walt Disney Studios, and 20th Century Fox, he brings broad experience in applying AI and analytics to solve complex problems across industries. He combines deep technical knowledge with a keen sense for practical, business-relevant AI applications, making him ideal to guide learners in mastering prompt engineering for generative AI tools.
No Code AI and Machine Learning Program by MIT Professional Education
No-Code AI is the revolutionary technology that empowers anyone, regardless of technical expertise, to build advanced AI-driven solutions effortlessly, democratizing innovation and accelerating digital transformation. Due to the advent of this technology, professionals skilled in the no-code approach are highly valuable to organizations across industries. In order to help you unlock the power of AI without coding, 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.
