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In this course, you will explore real-world use cases in artificial intelligence (AI), machine learning (ML), and generative artificial intelligence (generative AI) across a range of industries. These areas include healthcare, finance, marketing, entertainment, and more. You will also learn about AI, ML, and generative AI capabilities and limitations, model selection techniques, and key business metrics.

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Syllabus

Exploring Artificial Intelligence Use Cases and Applications

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops AI, ML, and generative AI foundations, which are core skills across a wide array of industries
Offers practical exploration of various industrial applications of AI, ML, and generative AI
Teaches real-world skills in AI, ML, and generative AI that are in high demand in modern job market
Emphasizes key business metrics, an essential aspect for evaluating AI, ML, and generative AI projects
Delivered by AWS instructors, who are seasoned experts in cloud computing and AI

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Exploring Artificial Intelligence Use Cases and Applications with these activities:
Follow the TensorFlow tutorials on machine learning
These tutorials will provide you with hands-on experience with machine learning using TensorFlow, the leading open-source machine learning library.
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  • Go through the TensorFlow tutorials.
  • Complete the exercises and assignments.
Read 'Artificial Intelligence: A Modern Approach' by Stuart J. Russell and Peter Norvig
This book provides a comprehensive overview of the field of artificial intelligence and machine learning, and will help you build a strong foundation for the course.
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  • Read the book from cover to cover.
  • Take notes on the key concepts.
  • Complete the exercises and assignments at the end of each chapter.
Join a study group to discuss the course material
This will allow you to discuss the course material with other students and get help with any concepts you are struggling with.
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  • Find a study group to join.
  • Participate in the study group discussions.
Four other activities
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Solve leetcode problems on machine learning
This practice will help you improve your problem-solving skills and reinforce the concepts you learn in the course.
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  • Solve leetcode problems on machine learning.
Build a machine learning model to predict customer churn
This project will allow you to apply the concepts you learn in the course to a real-world problem.
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  • Gather data on customer churn.
  • Clean and prepare the data.
  • Build a machine learning model to predict customer churn.
  • Evaluate the performance of the model.
  • Deploy the model to production.
Develop a mobile app that uses AI to recognize objects
This project will allow you to apply the concepts you learn in the course to a real-world problem and develop your mobile development skills.
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  • Design the app.
  • Develop the app.
  • Test the app.
  • Deploy the app.
Contribute to an open-source machine learning project
This will allow you to gain experience with open-source software development and contribute to the machine learning community.
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  • Find an open-source machine learning project to contribute to.
  • Submit a pull request to the project.

Career center

Learners who complete Exploring Artificial Intelligence Use Cases and Applications will develop knowledge and skills that may be useful to these careers:

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