Bring together software engineering, DevOps, and data engineering skills to manage ML experiments from end-to-end
Differentiate yourself from other ML practitioners by developing skills across the ML model deployment workflow
No more losing time to model configuration. Focus on improving your models and deploying them at scale
Train machine learning models using top frameworks like scikit-learn, XGBoost, Tensorflow, and PyTorch
This course is fantastic! It supplied our team with all the information needed to mature our machine learning process."
- James Walker, Sr. Software Engineer
"This course is a great starting point to get into AWS SageMaker. Luigi's step-by -step approach makes it a very effective course"
- Harini Kannan, Data Scientist
Introduction to SageMaker
Setting up your development environment
Interactive Model Training
I'm the Founder of MLinProduction.com.
I lead machine learning teams. In the past I've held roles as a data scientist, ML engineer, and data engineer. I've worked for large public companies and for tiny startups, taught graduate courses in data analysis and big data engineering, and have consulted for Fortune 100 companies.
I've had one consistent goal throughout my career: To build real machine learning systems that deliver massive amounts of business value. Now I'm teaching other ML practitioners how to do the same. I'm excited to be learning with you!
How do I enroll in the course? Enrollment can be completed via the course enrollment section here. Enroll today and use the discount code TWIML to get an additional 10% off!
What will I learn in this course? The techniques taught in this course will help you build scalable, efficient, and fault-tolerant machine learning systems. You will learn to use Amazon SageMaker to:
What does this course include? The hands-on resources and materials to enhance your learning throughout this course include:
How will this course benefit me and my career? The benefits of taking this course include:
Who is this course for? This course is designed for the following types of people:
How long will each course run? What is the level of effort expected? The study group for this course will kick-off at 9am PT / 12pm ET on August 8th. These hour and a half sessions will run for six consecutive weeks with a targeted completion date of September 12th.
Is there a discount for TWIML participants? Glad you asked. Yes, to kick off this partnership, Luigi has agreed to extend a discount to TWIML community members who register. Please use discount code TWIML when you enroll to get the TWIML community discount!
What programming languages/frameworks are used in this course? This course utilizes Python 3 as the main programming language. In order to interact with Amazon SageMaker, we rely on the SageMaker Python SDK and the SageMaker Experiments Python SDK. Additionally, we'll train models using the scikit-learn, XGBoost, Tensorflow, and PyTorch frameworks and associated Python clients.
Is TWIML paid as part of this arrangement? Yes, we are a Luigi Patruno / Teachable affiliate and get a commission as part of the partnership. Whatever we earn through this relationship will help support our broader community and educational efforts. That said, we would never recommend a course we didn’t think was a good use of your time and a good value.
How long will students have access to the course materials? After you enroll, you will have access to the materials indefinitely.
How long will enrollment for the course be open? How long will the discount be available? While the course itself is fundamentally designed for self-paced study, with Luigi running a live weekly study group, we will be closing enrollment on Friday, August 7th at 11:59 PT. The TWIML discount will be available until the close of enrollment.
Will the weekly study group sessions be open to anyone? Luigi's weekly study group sessions are intended for enrollees and will assume that learners have at least gone over that week’s lectures at a high level.
Is there a detailed syllabus? Yes, the syllabus can be found here.
What can I expect from the weekly online sessions? The weekly online sessions are live study group sessions presented by Luigi, the instructor and author of the Building, Deploying, and Monitoring Machine Learning Models with Amazon SageMaker course. At the sessions, Luigi will present a summary of that week’s course materials and open the floor for student discussion.
What if I cannot participate in the weekly online sessions? The weekly study group sessions will be recorded and will be available to TWIML enrollees.
What is the refund policy? There is a 14-day refund policy on the course.
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