Amazon Launched Free Certification Course in Machine Learning | AWS 3 Free Certificate | AWS Online Courses

Hello Skillers, This post to inform you about that Learn practical skills that will help you get the job you want in this free course by Amazon AWS. Upon completion of this course you will receive a free AWS certificate without testing.

About Course:

Amazon Web Services has introduced a free course aimed at business leaders and technology decision makers who plan to launch a machine learning strategy (ML) for their organizations.
In this three-subject curriculum, you will learn the best practices and recommendations for machine learning (ML). The tutorial explores how to map ML integration into your business processes, assesses requirements to determine if ML is the right solution to a business problem, and explains what is required for successful organizational acceptance of ML

• Level of study: Fundamental 
• Time: 90 minutes

Cost For the Course:

There is no any fee for attending this program.

Who Can Participate:

• All students from anywhere around the globe are welcome!
• Graduate Student  With Any Degree.
• Graduate Student For Any Degree.
• Anyone who wants to learn new skills.

How To Get Certificate:

Professionals and Students will receive a free certificate upon graduation. You Will Get Three-Certificate after completing 3 Modules, Technically You will get 3 Free AWS Certificate after completion.

Curriculum framework:

Course 1: Introduction to Machine Learning: The Art of Possible

Part 1. How can machine learning help?

      • Describe machine learning

      • Describe a good loop feedback (flywheel) that runs ML projects

      • Describe the various business domains that influence machine learning

      • Describe machine learning opportunities in underutilized markets

Part 2. How does machine learning work?

      • Describe artificial intelligence

      • Explain the difference between artificial intelligence and machine learning

Part 3. What are some of the potential problems with machine learning?

      • Explain the differences between simple and complex models

      • Understand the problems of ambiguity and uncertainty with machine learning models

Part 4. Conclusion

Course 2: Planning a Machine Learning Project

Part 1. Is machine learning a solution for my problem?

      • Explain how you can decide if ML is the right solution to your business problem

Part 2. Is my data ready to be read electronically?

      • Describe the process of verifying your data with ML

Part 3. How will machine learning affect the timeline of the project?

      • Explain how ML can affect the timeline of a project

Part 4. What are the first questions I should ask in a post?

      • Find questions to ask about ML shipping

Part 5. Conclusion

Course 3: Building a Machine Learning Organization

Part 1. How can I prepare my organization to use ML?

      • How can I prepare my organization to use ML?

      • How can AWS help me?

      • What are some strategies I can take to ensure the success of the organization?

      • What cultural change does my organization work for?

Part 2. How do I process my data plan?

      How do I process my data plan?

      • How can I improve my data strategy?

Part 3. How do I create a culture of learning and collaboration?

      • How do I develop the habit of reading and collaborating?

      • What is a data scientist?

      • What skills should a data scientist have?

      • What does the ML driver team look like?

      • What other support roles will I need?

      • What are the important tasks?

Part 4. How do I start my ML journey?

      • How do I start my ML journey?

      • What does the ML tour look like?

      • What is the business model of organizational progress?

Part 5. Conclusion

Signup LINK!!!

Here is video shows Step by Step Guide:

We Hope You Will Like Our Content Follow us for More Updates!!!