Artificial Intelligence (AI) for Managers - 2 Days

• No prerequisites required

Audience

• Business leaders
• Project managers

Artificial Intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and act like humans. It covers a variety of technologies, such as machine learning and deep learning, and is used for various business and corporate applications to solve organizational challenges and needs.

This instructor-led, live training (online or onsite) is aimed at managers and business leaders who wish to learn about the fundamentals of artificial intelligence and manage AI projects for their organization.

By the end of this training, participants will be able to understand AI at a technical level and strategize using their organization’s data and resources to successfully manage AI projects.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction

Overview of Artificial Intelligence (AI)

• Machine learning systems

Exploring Applications for AI

• AI in the corporate context

Learning About the Technology of AI

• Underfit and overfit, classification, and regularization
• Multi-layer perception (MLP) and deep learning
• Convolutional and recurrent neural networks

Assessing Strategic Approaches

• Commissioning or procurement (build or buy?)
• AI maturity models for your organization

Working With Data in Your Organization

• Data readiness evaluation
• Word embeddings
• Training with artificial data

Assessing AI Project Selection

• Key criteria for project selection

Managing an AI Project

• Machine learning versus deep learning
• Project management (lifecycle, timescales, methodology)
• Operations, maintenance, and risk management

Gathering Feedback

• Implementing feedback methods (surveys, interviews, etc.)
• Key stakeholders who will provide feedback
• Analyzing results

Summary and Next Steps