Foundations of Artificial Intelligence and Machine Learning (AI/ML)

This foundational course introduces the principles and practices of artificial intelligence and machine learning, with a focus on real-world applications in engineering, operations, and business strategy. Participants will explore supervised and unsupervised learning, model optimization, and data preparation through hands-on examples and case studies. Designed for both technical professionals and managers, the course bridges the gap between theory and implementation, enabling smarter, data-driven decision-making.

Learning Outcomes:

  • Understand and compare key AI and machine learning approaches, including their strengths, limitations, and use cases.
  • Train and evaluate machine learning models using supervised learning techniques and performance metrics.
  • Identify trade-offs in data collection, model complexity, and optimization strategies for real-world applications.

Who Should Attend:

  • Engineers, scientists, and technical professionals seeking to build foundational AI/ML knowledge.
  • Managers and team leaders who need to evaluate and implement AI/ML strategies in their organizations.
  • Professionals with a basic understanding of calculus, linear algebra, and statistics looking to apply data science in practice.
Date
Format
ID
Fee
 December 02-11, 2025
Live Online
ID: D801
Fee: $2,195%