AWS Certified Machine Learning Engineer
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Instructor-led | 6 weeks | 12 sessions (Sat & Sun)
AWS Certified Machine Learning Engineer
Overview
This accelerated course gives you a complete, practical, and beginner-friendly introduction to Machine Learning engineering on AWS. You will learn the full end-to-end ML lifecycle—from data ingestion and feature engineering to model training, deployment, and MLOps automation—using real AWS tools such as SageMaker, S3, IAM, Glue, Lambda, and EC2. Through instructor-led sessions and hands-on labs, you’ll build the skills needed to design scalable ML systems, optimize training workloads, deploy real-time inference endpoints, and manage ML pipelines at production scale.
Master the Power of Cloud with Confidence!
What You’ll Learn:
How the end-to-end ML workflow operates on AWS from data collection to monitoring
Building and managing high-quality ML data lakes using S3, Kinesis, and DataSync
Using AWS Glue, Athena, and SageMaker Feature Store for feature engineering and data preparation
Running scalable ML training jobs with built-in algorithms and deep learning frameworks
Optimizing models with hyperparameter tuning and distributed training
Deploying real-time inference APIs, serverless ML endpoints, and batch transform jobs
Why Choose This Course?
This course is designed for both beginners and working professionals, offering a clear, step-by-step learning path into AWS Machine Learning. Every session is fully instructor-led, supported by hands-on labs that walk you through real AWS services used by ML engineers today. CloudCollege’s structured approach has helped countless learners transition into ML and cloud engineering roles and this course is built to do the same for you.
Who Should Enroll ?
Perfect for Beginners
No prior ML or cloud experience needed. We start from fundamentals and guide you step-by-step.
Ideal for Developers & IT Professionals
Great for engineers and IT staff looking to transition into ML engineering roles.
ML Engineer Certification Ready
Aligned with the AWS ML Engineer – Associate exam to help you prepare confidently.
What Skills You’ll Cover From This Course
Master in-demand skills with hands-on learning.
Designing ML data lakes and ingestion pipelines on AWS
Feature engineering, ETL workflows, and schema validation
Configuring and running training jobs with SageMaker
Building ML models with XGBoost, TensorFlow, and PyTorch
Performing hyperparameter tuning and distributed training
Deploying ML models with real-time, batch, and serverless inference
Join Today and Shape Your Future in the Cloud !
This is more than just a course; it's your stepping stone to endless opportunities in the world of cloud computing. Whether you're aiming for a certification, a new job, or simply expanding your skill set, we’re here to guide you every step of the way. This is more than just a course; it's your stepping stone to endless opportunities in the world of cloud computing. Whether you're aiming for a certification, a new job, or simply expanding your skill set, we’re here to guide you every step of the way.
Any questions?
We got you
No. The course starts from the basics—making it suitable for complete beginners as well as professionals with limited ML experience.
Absolutely. The curriculum is aligned with the latest exam objectives and includes hands-on labs, real-world examples, and exam-focused guidance.
Hear From Our Learners
This course exceeded my expectations! The quizzes and projects helped reinforce every concept.
The perfect balance between professional-level content and beginner-friendly explanations. Highly valuable.
The instructor's passion for the subject really shines through. It made me excited to learn and apply the concepts.
I was skeptical at first, but this course delivered on every promise. The support from the instructor was outstanding.
Clear explanations, responsive support team, and great pacing. I've already applied what I learned in my job.
Every lesson builds perfectly on the previous one. The instructor anticipates questions and addresses them proactively.
Everything is laid out logically, making it easy to follow along. The supplementary materials are also excellent.
