Professional Training · Applied AI Engineering Track
Amazon SageMaker Studio for Data Scientists
A three-day, hands-on course for experienced data scientists. Building a model is only part of the job: this course shows how SageMaker Studio brings data preparation, experimentation, training, tuning, deployment, monitoring and resource management into a single integrated environment, so that the work either side of modelling stops being the slow part of the process.
Authorised Instructors
Eric Tai
Head, Technology
- Machine Learning Engineer – Associate
- Security – Specialty
- DevOps Engineer – Professional
- Solutions Architect – Professional
- +4 more
Hui Liang
Chief Digital Officer
- Machine Learning Engineer – Associate
- Security – Specialty
- Generative AI Developer – Professional
- Solutions Architect – Professional
- +5 more
Any of these AWS Authorised Instructors may deliver this class, depending on the scheduled run. Trainers confirmed on enrolment.
Who Should Attend
- Data Scientists: Experienced practitioners responsible for models end to end.
- Machine Learning Practitioners: Specialists proficient in ML and deep learning fundamentals.
- ML Engineers: Engineers supporting data scientists through the model lifecycle.
Prerequisites
This is an advanced course. To attend, you should have:
At least one year of experience as a data scientist training, tuning and deploying models.
Proficiency in machine learning and deep learning fundamentals.
Experience using machine learning frameworks and programming in Python.
Completion of AWS Technical Essentials, in digital or classroom form.
Learning Objectives
In this course, you will learn to:
Prepare data in Studio: Speed up dataset preparation within the integrated environment.
Build and experiment: Develop and compare models without leaving Studio.
Train and tune: Run training jobs and tune models efficiently.
Deploy solutions: Move trained models into serving environments.
Monitor performance: Track deployed models and act on what the monitoring shows.
Manage ML resources: Keep the underlying machine learning resources organised and under control.
Certification
A MY Code Campus certificate of completion is awarded for Amazon SageMaker Studio for Data Scientists.
In-person in Kuala Lumpur or live virtual. Team & enterprise rates available.