Master ML Project Planning with the Machine Learning Canvas

Plan better, implement faster

• Learn to structure and plan projects with the ML Canvas, a framework used by 10,000+ companies throughout the world

• Turn fluffy discussions into practical outcomes, and improve (remote) collaboration across disciplines

• Reduce implementation time: better specify what to build, anticipate key questions, and make your project a success!

Online course taught by Louis Dorard, author of the ML Canvas

course benefits

• 4 hours of videos & text lessons. Detailed explanations, illustrations, hands-on demos. Bite-sized learning pieces to share with your team.

• Case studies with example Machine Learning Canvases and how they were created

• Step-by-step process to create a detailed and bullet-proof Machine Learning Canvas, from your own use case idea

for Innovation & engineering managers

PLAN is our 2nd course. It’s made for Product Managers, Innovation Managers, R&D Project Managers, Engineering Managers, IT Architects, Consultants. You’ll gain the knowledge and skills to become the go-to person for starting and leading high-value ML projects in your organization.

Pre-requisites

• This course assumes non-technical knowledge of high-level ML concepts, possibilities, limitations

• It’s best if you also have one or more ML use case ideas, to which you'll apply the ML Canvas.

If you don’t have these pre-requisites, and you want to find the right use cases of your company, have a look at our 1st course: FIND.

WHAT YOU’LL LEARN

Data and models are artifacts — the real asset is the ML system. Learn how to design it properly. You will learn how to turn use case ideas into detailed specifications.

This course comprises 6 modules that will teach you the techniques that corporations, consultants, SME’s, schools, and startups have used to change the way they think about ML project planning:

1. Creating ML value — foundations

2. Elements of the ML Canvas — how to fill each “box”

3. Example ML Canvases — case studies

4. Towards a flawless design — avoiding common mistakes

5. Collaborating within a team — practical tips

6. Next steps — transitioning to implementation