Using and Understanding AI

Course schedule

Classroom Training:
DateVenueDurationPrice
10 - 14 Jun 2024London5 days£4,250
9 - 13 Sep 2024London5 days£4,250

Please note: prices shown above are exclusive of VAT (20%).

Course Overview

Unravel the complexities of AI with this course designed for professionals seeking to understand and apply AI technologies in their business operations and strategies.

Who Should Attend

This course is ideal for Directors of Operations, managers, and professionals across industries who are looking to enhance their knowledge of AI and its practical applications. It is suitable for individuals responsible for exploring AI solutions to improve business processes, enhance customer experiences, and gain competitive advantages through AI technologies.

Course Outcomes

  • Equip participants with a solid foundation in AI principles and concepts
  • Enable participants to identify AI opportunities in their organizations
  • Teach strategies for planning and implementing AI projects
  • Empower participants to make informed decisions about AI technologies

Course Topics

Introduction to Artificial Intelligence

  • Defining AI and its significance in the modern world
  • Historical evolution of AI
  • Types of AI (e.g. machine learning natural language processing)
  • Ethical considerations in AI

AI Technologies and Tools

  • Overview of AI technologies and frameworks
  • Case studies showcasing successful AI implementations
  • Identifying the right AI tools and platforms for specific tasks
  • AI standards and best practices.

Identifying AI Opportunities

  • Assessing processes for AI suitability
  • ROI analysis and cost-benefit considerations
  • AI project scoping and feasibility assessment
  • Identifying data sources and data quality considerations

Implementing AI Solutions

  • Planning and designing AI projects
  • Data collection preprocessing and feature engineering
  • Model training testing and validation
  • Deployment and integration of AI systems

Leveraging AI for Business Improvement

  • Monitoring and optimizing AI models
  • Data analytics and insights derived from AI
  • Scaling and expanding AI initiatives
  • Ethical and social implications of AI in business

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