Cohort-based Course
Learn how to manage data science teams and get models into production.
Cohort-based Course
Learn how to manage data science teams and get models into production.
Course overview
Data Science projects are full of uncertainty, making it impossible to plan everything without first doing something.
In this course, you will learn how to first target risk and benefit from having a fixed timeline and a flexible scope to finish significant data science projects in 6-week cycles.
Why should you trust us?
This course is based on the handbook we (Hakim and Wojtek) used at NannyML, a machine learning monitoring company with solid research foundations, to lead our research data science team. Over the last four years, we've refined it to address some of the most challenging research questions, resulting in the development of four novel ML monitoring algorithms that are now in production.
NannyML has been downloaded by over 500,000 people and is trusted by dozens of Fortune 500 companies. Our software stands out for its research-driven foundation, which is key to our ability to transition effectively from research to production.
Who should take this course?
— Lead Data Scientists, Data Science Managers, Heads of Data Science, or anyone leading a team that aims to put ML/AI models into production.
—Anyone who has struggled to put models into production in the past.
You should NOT take this course if:
— Your projects don't need any data science or machine learning.
— You are very early in your data science career.
If you're still interested and want to learn from people who have successfully deployed novel algorithms in 6-week cycles, read on.
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A data science leader looking to put models into production faster.
02
Tired of getting stuck in the POC phase.
03
Ready to lead your team in building a research process that enables them to deliver novel results.
Design and implement a six-week plan to get Data Science projects into production, focusing on sustainable and scalable practices.
Tackle Data Science management challenges like vague requirements, data leaks, and models getting stuck in the prototyping phase forever.
Understand the key differences between software engineering and data science projects, and explain why agile doesn't work for data science.
Adapt the "Shape Up" methodology for Data Science projects to ship models to production more frequently and efficiently.
Kick off your organization’s first project using a "Shape Up—like" methodology, and demonstrate its value through a successful pilot run.
Interactive live sessions
Lifetime access to course materials
20 in-depth lessons
Direct access to instructor
Projects to apply learnings
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
Research to Deployment: Get AI into the Real World
Tuba Dikici
CEO at NannyML
Co-founder At NannyML, one of the most popular ML monitoring tools. He has almost a decade of data science experience. Hakim holds a Masters Degree in Bioinformatics from the KU Leuven.
CTO at NannyML
Wojtek is an AI professional and entrepreneur with a master's degree in AI from KU Leuven. He co-founded NannyML, an OSS Python library for ML monitoring and post-deployment data science. As the CTO, he leads the research and product teams, contributing to the development of novel algorithms in model monitoring.
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2-3 hours per week
Weekly sessions
5:00pm - 6:30pm CET
We meet every Thursday from October 24 to December 12.
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you
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