Developing an AI/ML Data Strategy: Building an AI-powered Workforce

Data analytics 2022    |    Intermediate
  • 11 videos | 45m 44s
  • Includes Assessment
  • Earns a Badge
Rating 4.7 of 100 users Rating 4.7 of 100 users (100)
Building a successful data team is a key part of a data strategy. To build proper data teams, it's important to know how they are structured and the roles of each member. Through this course, learn how to build an AI-powered workforce with a data team. Discover the need for an AI-powered workforce and three main structure types of a data team. Learn how to determine which strategy is preferable for a data team. Next, explore the potential shifts in job roles and responsibilities due to AI integration, the role of managers in driving AI adoption and change management, and strategies for fostering a culture of innovation and AI awareness within the workforce. Finally, explore the roles of data team members, how to evaluate an organization's strategy, and how to move an organization toward a data-driven culture. After course completion, you'll be able to outline the functions and best practices for a data team.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Identify the need for building an ai-powered workforce
    Identify the potential shifts in job roles and responsibilities due to ai integration
    Distinguish between centralized, decentralized, and hybrid data team structures and the benefits and challenges of each structure type
    Describe the role of managers in driving ai adoption and change management
    Compare the three options for building a data science team
  • Name the roles of the data science team and the tools they use
    Identify an organization's data-driven culture and ai strategy
    Outline how to move an organization toward a more data-driven culture
    Outline strategies for fostering a culture of innovation and ai awareness within the workforce
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 53s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 4m 14s
    After completing this video, you will be able to identify the need for building an AI-powered workforce. FREE ACCESS
  • Locked
    3.  Changes in the Workforce with AI Integration
    5m 47s
    Upon completion of this video, you will be able to identify the potential shifts in job roles and responsibilities due to AI integration. FREE ACCESS
  • Locked
    4.  Data Science Team Structures
    2m 52s
    In this video, learn how to distinguish between centralized, decentralized, and hybrid data team structures and the benefits and challenges of each structure type. FREE ACCESS
  • Locked
    5.  The Manager's Role in AI Adoption
    6m 18s
    Upon completion of this video, you will be able to describe the role of managers in driving AI adoption and change management. FREE ACCESS
  • Locked
    6.  Hiring vs. Contracting vs. Training Data Teams
    3m 52s
    Upon completion of this video, you will be able to compare the three options for building a data science team. FREE ACCESS
  • Locked
    7.  Data Team Roles
    4m 36s
    After completing this video, you will be able to name the roles of the data science team and the tools they use. FREE ACCESS
  • Locked
    8.  Data-driven Culture and AI Strategy
    5m 46s
    During this video, discover how to identify an organization's data-driven culture and AI strategy. FREE ACCESS
  • Locked
    9.  Move toward a Data-driven Culture
    5m 23s
    Upon completion of this video, you will be able to outline how to move an organization toward a more data-driven culture. FREE ACCESS
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    10.  Strategies for Fostering a Culture of Innovation
    5m
    In this video, learn how to outline strategies for fostering a culture of innovation and AI awareness within the workforce. FREE ACCESS
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    11.  Course Summary
    1m 3s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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