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In this course, you will learn about best practices and recommendations for machine learning (ML). The course explores how to roadmap for integrating ML into your business processes, explores requirements to determine if ML is the appropriate solution to a business problem, and describes what components are needed for a successful organizational adoption of ML.

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In this course, you will learn about best practices and recommendations for machine learning (ML). The course explores how to roadmap for integrating ML into your business processes, explores requirements to determine if ML is the appropriate solution to a business problem, and describes what components are needed for a successful organizational adoption of ML.

We recommend that attendees of this course have:

• Basic knowledge of computers and computer systems

• Some basic knowledge of the concept of machine learning 

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What's inside

Syllabus

Machine Learning Essentials for Business and Technical Decision Makers

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by AWS instructors, who are recognized for their work in the field of machine learning
Explores various aspects and applications of machine learning across different industries and domains
Strong emphasis on best practices and recommendations for implementing machine learning solutions effectively
Teaches learners how to evaluate if machine learning is the right solution for specific business problems
Covers key considerations for successful organizational adoption of machine learning
Designed for learners with basic knowledge of computers and machine learning concepts

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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 Machine Learning for Business & Technical Decision Makers with these activities:
Review Machine Learning Concepts
Reviewing machine learning concepts will help you build a stronger foundation and better prepare you for the course.
Browse courses on Machine Learning
Show steps
  • Read introductory articles or blog posts about machine learning.
  • Watch videos or tutorials on machine learning basics.
  • Complete practice exercises or quizzes to test your understanding.
Join a Study Group or Discussion Forum
Participating in a study group or discussion forum will allow you to connect with other students, share knowledge, and clarify concepts.
Show steps
  • Identify study groups or discussion forums related to machine learning.
  • Join the group or forum and actively participate in discussions.
  • Ask questions, share insights, and help others.
Follow Tutorials on Machine Learning Algorithms
Following tutorials on machine learning algorithms will help you develop practical skills and deepen your understanding of different algorithms.
Show steps
  • Identify machine learning algorithms that are relevant to the course.
  • Find tutorials or online courses that cover these algorithms.
  • Follow the tutorials step-by-step and implement the algorithms.
  • Test the algorithms on sample datasets.
Three other activities
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Solve Machine Learning Practice Problems
Solving machine learning practice problems will improve your problem-solving skills and reinforce your knowledge.
Browse courses on Coding Challenges
Show steps
  • Find practice problems or coding challenges related to machine learning.
  • Attempt to solve the problems independently.
  • Compare your solutions with others or seek help if needed.
Create a Machine Learning Project Presentation
Creating a machine learning project presentation will help you synthesize your knowledge, develop communication skills, and showcase your understanding.
Show steps
  • Choose a machine learning project to work on.
  • Implement the project and collect results.
  • Create a presentation that explains the project, methods, and outcomes.
  • Present your project to your peers or instructors.
Start a Personal Machine Learning Project
Starting a personal machine learning project will allow you to apply your skills, explore your interests, and build a portfolio.
Show steps
  • Identify a problem or domain you are interested in.
  • Gather data and explore different machine learning algorithms.
  • Implement and evaluate a machine learning model.
  • Deploy or share your project.

Career center

Learners who complete Machine Learning for Business & Technical Decision Makers will develop knowledge and skills that may be useful to these careers:

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