ML Technician Certification Course

Develop your ML expertise in 9 weeks

The demand for AI and machine learning (ML) expertise is growing across all industries -- and so is the demand for skilled workers.

The ML Technician Certification Course gives individuals the skills they need to thrive as they pursue a career in AI or integrate ML into their current role.

Part on-demand lessons, part live online classes and part collaborative project, the 9-week course is a fast and flexible way to develop your ML knowledge and skills.

You'll leave the course with:

An electronic ML Technician Badge to share on Linkedin and beyond
A Certificate of Completion
A Capstone Project to share with prospective employers

Classes begin on January 31, 2023.

Course information

This project-based course takes a flipped classroom approach.

Each week, students will take in the content through Amii’s learning management system (LMS). The content is then reviewed and practiced with the instructor in a live synchronous class.

Live office hours, programming labs and group work highlight the learner experience.

There is a module and programming assignment every two weeks, and the course concludes with a capstone project. Participants should expect to spend 10-14 hours on coursework per week.

The ML Technician Certification runs for $4,995 CAD.

View the Program Guide

Who should take this course?

This course has been created to upskill anyone with a basic technical skillset. For example, if you have previously obtained an engineering degree, you will already have the numerical sense necessary for acquiring knowledge of machine learning.

In addition, we expect that the learner will have background and experience with the following skills and concepts:

Basic calculus
Programming in Python
Matrix calculations
Probabilistic reasoning

Participants in this course are required to attend Amii’s ML Foundations 1 & ML Foundations 2 before the course start – successful applicants for the ML Tech Certification will receive complimentary access to the Foundations courses. Previous attendance in ML Foundations applies.

Scholarships available

Amii is offering a limited number of scholarships which cover the full cost of registration.

The focus is on giving access to individuals who are typically underrepresented in STEM fields, who are recent immigrants to Canada or who live in rural settings.

Applications are completed on the basis of self-identification. If you would like to apply for a scholarship, fill out the Financial Assistance section of the program application.

What will I learn?

You’ll graduate from the course with:
A science-based understanding of what machine learning is and how it works
The skills to confidently create a business case for a ML project at your company
The ability to undertake an ML project or apply for a job with AI/ML requirements
Hands-on experience with all stages of a machine learning project: from objective definition and data preparation; through model selection and tuning; to building an ML proof-of-concept.
Course objectives include:
Identify and scope an ML problem that aligns with your organization’s business outcomes
Pre-process, collect and summarize the most appropriate real-world data for your model
Build the right model for your business problem by using sound estimation principles and accurately evaluating the performance of your ML model
Understand the science of machine learning, where it comes from and how it works
Apply Amii’s ML frameworks that support the effective and efficient development of ML models

Meet your expert instructor

Our instructors have a passion for teaching with a background in advanced AI and machine learning research. They've studied under some of the world's top AI researchers, and they're excited to share their knowledge with you!

Mohammad M. Ajallooeian is a Machine Learning Educator & Scientist at Amii. He has been researching and teaching AI and ML for 15 years and is currently pursuing a PhD in Computing Science at the University of Alberta specializing in Statistical Machine Learning.