Week 3 focuses on the structured process of developing and deploying AI solutions, ensuring alignment with business objectives. Learners will explore the full AI model lifecycle, from understanding business needs to maintaining AI models in production. The emphasis is on practical implementation, guiding participants through key stages such as model selection, validation, deployment, and continuous monitoring.

Learning Goals

  • Understand the AI Model Lifecycle
    Gain insight into the structured phases of AI development, from identifying business needs to deploying and maintaining AI systems.
  • Define Business Problems for AI Applications
    Learn to assess and formalize business needs, ensuring AI adoption aligns with strategic goals.
  • Explore Model Selection and Development
    Identify the appropriate AI models (classification, regression, clustering) based on specific business challenges.
  • Learn Data Preparation and Feature Engineering
    Understand techniques for cleaning, transforming, and engineering data to enhance model performance.
  • Validate and Assess AI Models
    Use performance metrics and validation techniques to ensure AI models generalize effectively and avoid overfitting.
  • Deploy AI Solutions in Business Environments
    Understand the steps involved in operationalizing AI models, integrating them into business workflows, and ensuring usability.
  • Monitor and Maintain AI Systems
    Learn strategies for tracking AI model performance, identifying data drift, and continuously improving deployed solutions.
By the end of this week, participants will have a strong understanding of AI project execution, focusing on both technical rigor and business impact.