Implementing AI Solutions in Business
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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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.For Business
Training 2 or more people?
Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and moreIn the following Tracks
AI Business Fundamentals
Go To Track- 1
Getting Started with AI
FreeLearn 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.
Overview of AI50 xpDo you know AI?50 xpThe phases of an AI solution100 xp10,000 ft view: how does AI work?50 xpStill know AI?50 xpGenerative AI vs. Other AI100 xpComponents of an AI solution50 xpResponsible AI50 xpWhy is Responsible AI important?50 xpCommon Principles of Responsible AI100 xpAssessing risk for a new AI solution50 xp - 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.
The benefits of AI for a business50 xpPillars of AI Value50 xpBusiness value or nice to have?100 xpLimitations of AI50 xpIdentify limitations of AI50 xpLimitation or benefit?100 xpHuman-in-the-loop50 xpUse cases for AI50 xpCommon business use cases100 xpAI advantage in a scenario50 xpIdentify a use case for AI50 xpPrinciples of a good use case50 xpClassify use cases100 xpDeconstructing a task50 xp - 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.
Getting started with a POC50 xpPhases of a POC100 xpWhat makes a successful POC?50 xpQuestions to clarify goals100 xpData50 xpImportance of data50 xpProfiling and evaluating data100 xpBiased data50 xpInfrastructure50 xpQuestions about the POC infrastructure100 xpThe AI development environment50 xpBuy or build?100 xpBuilding the project team50 xpTypes of roles50 xpResponsibilities100 xp - 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.
Measuring the POC50 xpWhat makes a POC successful?50 xpClassifying metrics in e-commerce scenario100 xpAssessing the POC50 xpComponents for scaling100 xpBalancing value and feasibility50 xpMake a decision about scaling50 xpConsiderations for full implementation50 xpFocus areas for a full implementation50 xpMonitoring and model drift50 xpDevOps, MLOps, or compliance?100 xpAdoption and skilling50 xpReasons for no financial benefits50 xpResistance to AI100 xpBenefits for change management, culture, and upskilling100 xpWrap-up50 xp
For Business
Training 2 or more people?
Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and moreIn the following Tracks
AI Business Fundamentals
Go To Trackcollaborators
Jacob Marquez
See MoreData 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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