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Artificial Intelligence (AI) Strategy

Course Summary

The Arificial Intelligence (AI) Strategy course provides the participants with a foundation for building a successful AI program within the enterprise. Participants will be introduced to key elements that the role performs, what a strategy should entail and how to implement an AI plan. The course concludes with an understanding of tasks and characteristics needed to lead a successful AI program.

Purpose
Gain an understanding of key elements needed for building and leading an enterprise AI strategy.
Audience
Anyone interested in aspiring to an AI strategy role.
Role
Data Scientist | Data Engineer | Business Leader
Skill level
Intermediate
Prerequisites
Basic understanding of core AI technologies, data, and business process
Duration
3 days
Related technologies
AI/ML | Agile | Database Tools

 

Learning objectives
  • Identify the core requirements and tools needed for building an AI strategy.
  • Understand the importance of data when building an AI strategy.
  • Be able to construct key elements for implementing a successful strategy.
  • Develop a change agent mentality for building effective teams and leading an AI prgoram cross-functionally within the enterprise.

What you'll learn:

In this course, you'll learn:
 
  • Defining the Role of an AI Strategist
    • Introduction to AI Strategy
      • What is an AI Strategy?
      • Integrating AI Strategy with the Enterprise
    • Defining the Role
      • Key Responsibilities for an AI Strategist
      • Core Foundational Skills
    • AI Technologies
      • Core Concepts
      • Tools and Platforms
    • Business and Industry Applications
    • Data Strategy and Management
      • Importance
      • Types: structured, unstructured
    • Data Collection and Cleansing
    • Data Governance
      • Privacy/security
      • Regulatory compliance
      • Ethics in AI
  • Building a Successful AI Program
    •  Developing an AI strategy
      • Assessing organizational readiness
      • Setting AI goals and objectives
        • Aligning to business objectives
        • Defining measurable outcomes
      • AI Roadmap
        • Short/long term goals
        • Milestones/deliverab
      •  Resources
        • Budgeting
        • Talent – Hiring | Training | Building a Team
        • Risk/mitigation management
    • Implementing an AI Solution
      • Understanding Agile to manage AI projects
      • Prototyping and testing
      • Deployment and scaling
    • Monitoring an AI project
      •  Performance metrics and KPIs
      • Tracking performance
      • Continuous improvement
  • Leading an AI Program 
    • Being a Change Agent
    • Building and Leading Teams
    • Ethics and social impact
      • AI principles
        • Fairness, accountability, transparency
      • Mitigating Bias
      • Understanding potential societal impact
        • Job displacement
        • Job creation
    • Effective communication
      • Creating an AI culture
      • Working with the executive team
        • Communicating strategy and alignment to business
        • Building buy-in and stakeholder support
    •  Leading teams

Artificial Intelligence (AI) Strategy

real world content

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
expert practitioners

Expert Practitioners

Industry experts that bring their battle scars into the classroom.
experiential learning

Experiential Learning

More coding than lecture, coupled with architectural and design discussions.
fully customized

Tailored Outlines

Once-size-fits-all doesn't apply to training teams. That's where we come in!

Dive in and learn more

When transforming your workforce, it’s important to have expert advice and tailored solutions. We can help. Tell us your unique needs and we'll explore ways to address them.

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