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Implementing AI Solutions in Business

4.5+
14 reviews
Beginner

Discover how to extract business value from AI. Learn to scope opportunities for AI, create POCs, implement solutions, and develop an AI strategy.

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2 Hours16 Videos56 Exercises
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Course Description

Discover how AI can deliver business value

The latest AI tools and technologies, such as ChatGPT, have truly spectacular capabilities, but how does this translate into business value? In this course, you’ll learn about the capabilities and limitations of AI and how it can improve employee productivity, automate business processes, and provide better, more personalized customer experiences.

Learn how to build an AI Proof of Concept (POC)

The most amazing AI products and services likely started out as basic proof of concepts (POCs). You’ll learn about the various stages and personas involved with creating a POC, all the way from scoping opportunities to building a project team and understanding resource limitations. You’ll also learn about data management, storage, and privacy to ensure that your POC is compliant with the relevant governing regulations.

Build a case for AI implementation in the business

A single AI POC is often the start of a much wider discussion on implementing more AI solutions across the business. In this course, you’ll understand when and how to turn a POC into a full-fledged solution, how to identify points of resistance to AI adoption, and how to communicate the value of AI to the wider business and customers.
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In the following Tracks

AI Business Fundamentals

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  1. 1

    Getting Started with AI

    Free

    Learn what AI is, how it has evolved, and how it is different from other non-AI data solutions. In this chapter, you will begin building a framework for how to implement AI into your business, including key elements to an AI strategy, phases for implementation, and basic technical design. Finally, you'll learn about the importance of Responsible AI governance throughout the entire process.

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    Overview of AI
    50 xp
    Do you know AI?
    50 xp
    The phases of an AI solution
    100 xp
    10,000 ft view: how does AI work?
    50 xp
    Still know AI?
    50 xp
    Generative AI vs. Other AI
    100 xp
    Components of an AI solution
    50 xp
    Responsible AI
    50 xp
    Why is Responsible AI important?
    50 xp
    Common Principles of Responsible AI
    100 xp
    Assessing risk for a new AI solution
    50 xp
  2. 2

    Benefits, Limitations, and Use Cases of AI

    You now know what AI is and how to think about it responsibly. It's time to gain a better sense of its benefits, limitations, and use cases in business. In this chapter, you'll do just that! You'll understand the value AI can bring to an organization as well as the areas it lacks in. You'll go through some high-level use cases across different departments in a business. Finally, you'll learn about principles for choosing a great use case for an AI solution.

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  3. 3

    Building a Proof of Concept

    With use cases in mind, it's time to build a proof of concept! This is a small project that will determine the feasibility and estimate further business value if fully implemented. In this chapter, you will learn the phases of a POC, what makes them successful, and the important components to think about regarding technical infrastructure and data. Finally, you'll learn about the types of roles required for your POC project team.

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  4. 4

    Beyond the POC

    In this final chapter of the course, you will learn the final steps of an AI solution implementation - assessing the POC, scaling, and aligning culture and skills. You will understand the areas in which a POC can be evaluated as well as what are good indicators for moving forward with scaling the solution. You will go over the big components to focus on for scaling to a full implementation, including requirements for culture and upskilling folks in your business.

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For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

AI Business Fundamentals

Go To Track

Collaborators

Collaborator's avatar
Amy Peterson
Collaborator's avatar
James Chapman
Jacob Marquez HeadshotJacob Marquez

Data Scientist at Microsoft

Jacob H. Marquez is an insatiable learner and lifelong builder. He is a data scientist by day, answering audacious questions to support customer experience and company goals. He is a serial hobbyist by day and night: being an educator, building a coffee recommendation app, drinking coffee, writing on Medium, and amateur cycling and muay thai. He has a bachelor's in psychology and a master's in computational analytics (2024).
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Don’t just take our word for it

*4.5
from 14 reviews
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  • Kong C.
    9 months

    Useful as an awareness piece

  • Viacheslav K.
    10 months

    Thanks for usefull info ! Its really nice that authors are updating the facts and results of surveys!

  • Stephan K.
    10 months

    Great overview. Would be great to have additional trainings in this direction in the future.

  • Hossam M.
    10 months

    Very good

  • Sharon P.
    7 months

    Easy to understand but i need more content to grasp

"Useful as an awareness piece"

Kong C.

"Thanks for usefull info ! Its really nice that authors are updating the facts and results of surveys!"

Viacheslav K.

"Great overview. Would be great to have additional trainings in this direction in the future."

Stephan K.

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