"AWS: Fundamentals of Machine Learning & MLOps is the first course of Exam Prep (MLA-C01): AWS Certified Machine Learning Engineer – Associate Specialization. This course assists learners in building foundational knowledge of core machine learning concepts, including types of learning, data preparation, model evaluation, and operationalization. Learners gain a strong understanding of the difference between AI, Deep Learning, and Machine Learning, and how to identify and apply real-world ML use cases using AWS services.
AWS: Machine Learning & MLOps Foundations
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AWS: Machine Learning & MLOps Foundations
This course is part of Exam Prep MLA-C01: AWS Machine Learning Engineer Assocaite Specialization
Instructor: Whizlabs Instructor
Included with 
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
5 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Explore the core concepts of Machine Learning and how it differs from AI and Deep Learning.
Introduce key AWS services and MLOps practices for managing the end-to-end ML lifecycle.
Explore how to build and evaluate classification and regression models using AWS ML services.
Differentiate between batch and real-time inferencing methods and identify suitable use cases for each.
Skills you'll gain
- Regression Analysis
- Applied Machine Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- AWS SageMaker
- Data Cleansing
- Unsupervised Learning
- Machine Learning
- Supervised Learning
- Continuous Deployment
- Feature Engineering
- Data Processing
- Predictive Modeling
- MLOps (Machine Learning Operations)
- Amazon Web Services
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
September 2025
Assessments
4 assignments
Taught in English
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This course is part of the Exam Prep MLA-C01: AWS Machine Learning Engineer Assocaite Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 2 modules in this course
Welcome to Week 1 of the AWS: Machine Learning & MLOps Foundations course. This week, you’ll explore the fundamentals of Machine Learning (ML) and how it differs from AI and Deep Learning. We'll cover types of data, types of ML (supervised, unsupervised, reinforcement), and how to identify suitable ML use cases. You’ll walk through the ML lifecycle—from data ingestion to deployment—and get introduced to key AWS services that support ML workflows. We’ll also touch on MLOps concepts and AWS tools that help scale and manage ML models in production.
What's included
9 videos2 readings2 assignments1 discussion prompt
Welcome to Week 2 of the AWS: Machine Learning & MLOps Foundations course. This week, we’ll dive into practical aspects of model building. You'll start with a classification demo, followed by learning how to select, train, and evaluate models using AWS tools. We’ll cover data preprocessing techniques, explore the confusion matrix and regression metrics, and introduce unsupervised learning through clustering. Finally, you'll understand the difference between batch and real-time inferencing, and when to apply each.
What's included
9 videos3 readings2 assignments
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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