Course Overview
This AWS ML Engineer Associate Training programme is designed for professionals looking to build, train, and deploy machine learning models on AWS. Aligned with the MLA-C01 certification objectives, the course provides a structured pathway into practical machine learning engineering in cloud environments.
Through mentor-led sessions and practical scenarios, learners will prepare datasets, train models, and deploy scalable ML solutions using Amazon SageMaker and other AWS AI services. The course focuses on real-world workflows including feature engineering, model evaluation, and production deployment.
By the end of the programme, participants will be able to implement end-to-end ML pipelines, manage model lifecycle processes, and optimise performance and cost in AWS environments. This course supports professionals in data science, ML engineering, and AI development roles.
Hands-On Learning
Labs on SageMaker model training, deployment, and ML pipeline workflows
Mentor-Led Sessions
Expert-led sessions with real-world machine learning scenarios on AWS
Career-Ready Skills
Machine learning engineering and cloud deployment expertise
Learning Outcomes
Design end-to-end ML pipelines
Implement model training and deployment
Analyse model performance and accuracy
Evaluate data preparation techniques
Manage ML lifecycle and operations
Communicate ML solutions effectively
Prerequisites
Basic understanding of machine learning concepts
Familiarity with AWS services
Knowledge of Python or data tools
Detailed Syllabus
Organized by professional domains with comprehensive coverage
Topics Covered:
- •Data sources and ingestion
- •Data cleaning and preprocessing
- •Feature selection and engineering
Skills You'll Gain
Master these in-demand skills through hands-on practice
Career Progression
A clear view of the roles this programme supports, what typically comes next, and where learners progress over time
Ways to Learn
Choose the learning format that works best for you and your team
Live Online
Instructor-Led Training
Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
- Live instructor interaction (real-time)
- Trainer-led walkthroughs and real examples
- Guided resources and session notes provided
- Structured Q&A and practical discussion
Price per person
Group enrolments and early planning options available.
All prices are exclusive of VAT where applicable. Group enrolments and custom packages available on request.
Prefer a Faster, Personalised Route into IT?
Not everyone learns best in a group. If you want focused guidance, faster clarity, and confidence you can use on the job, our 1-to-1 Fast-Track Training gives you private, mentor-led support tailored to your experience and goals.
"Many learners choose 1-to-1 when they want understanding, not memorisation."
Exam & Certification Information
Everything you need to know about the certification exams
Important Information
This programme is aligned with the official exam objectives. Exam registration and certification are managed directly by the awarding body.
Credential
Certificate of Completion
On successful completion of AWS ML Engineer Associate Training, learners receive an Xcademia Certificate of Completion. This standalone certificate is issued directly by Xcademia and is aligned with globally recognised frameworks and best practices.
Frequently Asked Questions
Everything you need to know about this course
Yes, it is aligned with the MLA-C01 exam objectives.
Ready to Start Your Learning Journey?
Take the next step in your professional development