Theory | Hands-On Labs | Full Practice Exam with Explanations | Downloadable PDF Slides | Pass the certification exam
Sub Category
- IT Certifications
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Objectives
- Master key AWS ML services including SageMaker, Bedrock, and Comprehend through hands-on demonstrations and practical implementation.
- Design, deploy, and monitor machine learning pipelines on AWS using services like CloudWatch, CloudTrail, and SageMaker Model Monitor.
- Implement data preparation workflows using AWS analytics services including Glue, EMR, and Athena for effective ML model development.
- Develop secure and cost-effective ML solutions by implementing best practices in IAM policies, encryption, and resource optimization.
Pre Requisites
- Basic cloud computing knowledge is helpful but not required. This course is designed for IT professionals with some programming experience in Python, Java, or similar languages. Familiarity with data concepts and AWS fundamentals is beneficial, but comprehensive hands-on demonstrations will guide you through each service. You'll need an AWS account (free tier is sufficient) and a computer with internet access to follow along with the practical exercises.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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