Fundamentals of AI & ML: Introduction to Artificial Intelligence

Artificial Intelligence    |    Intermediate
  • 15 videos | 1h 4m 20s
  • Includes Assessment
  • Earns a Badge
  • Certification PMI PDU
Rating 4.4 of 2070 users Rating 4.4 of 2070 users (2070)
Artificial intelligence (AI) provides cutting-edge tools to help organizations predict behaviors, identify key patterns, and drive decision-making in a world that is increasingly made up of data. In this course, you will explore the full definition of AI, how it works, and when it can be used, focusing on informative use cases. You will identify the types of data, as well as the tools and technologies AI uses to operate. Next, you will discover a framework for using the AI life cycle and data science process. Then you will examine how data science, machine learning (ML), and AI are relevant in the modern business landscape. Finally, you will investigate the key differences between AI and traditional programming approaches, the benefits and challenges associated with integrating AI and ML into business approaches, and the potential impact of AI on job roles and workforce dynamics. Upon completion of this course, you'll be familiar with common concepts and use cases of artificial intelligence (AI) and be able to outline strategies for each part of the AI life cycle.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Identify concepts and use cases for artificial intelligence (ai)
    Identify use cases for ai and how ai can be used in your industry
    Identify the types of data that are used with ai and evaluate the importance of data quality and quantity in successful ai implementations
    Identify ai tools and technologies
    Outline the ai life cycle and its elements
    Outline how to develop specific, measurable, and objective questions for your organization
    Recognize how to get the right data for your ai project
  • Identify which methods to use and what questions to ask during the model, validate, and test stages
    Outline strategies for interpreting the results of an ai project using visualizations and domain knowledge
    Outline how data science (ds), machine learning (ml), and ai are relevant in the modern business landscape
    Recognize the key differences between ai and traditional programming approaches
    Outline the benefits and challenges associated with integrating ai and ml into business approaches
    Illustrate the potential impact of ai on job roles and workforce dynamics
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 13s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 4m 53s
    After completing this video, you will be able to identify concepts and use cases for AI. FREE ACCESS
  • Locked
    3.  What Can AI Do?
    5m 58s
    Upon completion of this video, you will be able to identify use cases for AI and describe how AI can be used in your industry. FREE ACCESS
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    4.  How AI Works: Data
    7m 58s
    After completing this video, you will be able to identify the types of data that are used with AI and evaluate the importance of data quality and quantity in successful AI implementations. FREE ACCESS
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    5.  How AI Works: Tools and Technologies
    4m 37s
    Upon completion of this video, you will be able to identify AI tools and technologies. FREE ACCESS
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    6.  Artificial Intelligence Life Cycle
    3m 6s
    After completing this video, you will be able to outline the AI life cycle and its elements. FREE ACCESS
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    7.  Data Science Process: Ask
    2m 15s
    Upon completion of this video, you will be able to outline how to develop specific, measurable, and objective questions for your organization. FREE ACCESS
  • Locked
    8.  Data Science Process: Research
    5m 40s
    After completing this video, you will be able to recognize how to get the right data for your AI project. FREE ACCESS
  • Locked
    9.  Data Science Process: Model, Validate, and Test
    4m 52s
    Upon completion of this video, you will be able to identify which methods to use and what questions to ask during the model, validate, and test stages. FREE ACCESS
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    10.  Data Science Process: Interpret
    4m 46s
    After completing this video, you will be able to outline strategies for interpreting the results of an AI project using visualizations and domain knowledge. FREE ACCESS
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    11.  DS, ML, and AI in the Business Landscape
    3m 17s
    After completing this video, you will be able to outline how data science (DS), machine learning (ML), and AI are relevant in the modern business landscape. FREE ACCESS
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    12.  What Sets AI Apart?
    4m 20s
    Upon completion of this video, you will be able to recognize the key differences between AI and traditional programming approaches. FREE ACCESS
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    13.  Integrating AI and ML into Business
    6m 14s
    After completing this video, you will be able to outline the benefits and challenges associated with integrating AI and ML into business approaches. FREE ACCESS
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    14.  Impact of AI and Generative AI on Workforce Dynamics
    4m 20s
    Upon completion of this video, you will be able to illustrate the potential impact of AI on job roles and workforce dynamics. FREE ACCESS
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    15.  Course Summary
    51s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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