Artificial Intelligence (AI) and Machine Learning (ML)

  • Artificial Intelligence (AI) and Machine Learning (ML)
  • Italy - Milan

Artificial Intelligence (AI) and Machine Learning (ML)

Course Category : Artificial Intelligence

An advanced programme providing a comprehensive understanding of Artificial Intelligence and Machine Learning concepts and their organisational applications for innovation and data-driven decision-making..

Starts On

21 - September - 2026

Ends On

25 - September - 2026

Location

Italy - Milan

Language

English

View the course details and register to enroll.

Register Now

View Course Introductory PDF

Targeted Audience

  • Digital Transformation Managers
  • Information Technology Managers
  • Data Analysts
  • Innovation and Development Specialists
  • Executives and Decision-Makers
  • Technology Project Managers
  • Professionals Interested in AI Applications

Targeted Skills

  • Understanding AI and ML Concepts
  • Differentiating Machine Learning Algorithms
  • Analysing AI Business Applications
  • Evaluating Opportunities and Risks
  • Understanding AI Governance and Ethics
  • Supporting Data-Driven Digital Initiatives

Expected Outcomes

  • Understand the fundamentals of AI and Machine Learning.
  • Identify major intelligent models and algorithms.
  • Evaluate AI applications across industries.
  • Understand the AI project lifecycle.
  • Comprehend AI governance and ethical principles.
  • Support organisational innovation and digital transformation initiatives.

Training Topics Index

  • Evolution of Artificial Intelligence
  • Core concepts and terminology
  • AI, Machine Learning, and Deep Learning distinctions
  • Intelligent systems and applications

  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning applications
  • Model selection and evaluation

  • Importance of data in AI systems
  • Data collection, preparation, and analysis
  • AI project lifecycle management
  • Data quality and governance challenges

  • AI in business and operations
  • Predictive analytics and decision-making
  • Intelligent automation and efficiency improvement
  • AI-driven innovation and digital transformation

  • AI ethics and responsible use
  • Risk management and governance
  • Privacy and security considerations
  • Emerging trends and future developments