Get a.head() in your career as Data Scientist
Being an expert is not the same as being a leader
Being a lead data scientist is not always about bringing the best technical solution to the table. You have to lead your team and stakeholders through the project, enhancing their impact through your guidance.
53% of data projects never goes to production.
Make your hitrate 100%.
In the course, we cover how to find potential data projects and the steps needed to select the ones with highest Return on Investment.
Increase your teams ROI
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Learn how to lead a team
Successful data projects require a team with different skills and expertise. Learn the different roles and how they impact the project.
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Course is in commuter friendly format
All lessions are bite-size friendly, perfect for the commute (or toilet break...)
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Hi, I'm Daniel!
I've worked both as AI & BI consultant at Accenture and as in-house data product owner for a Data & AI team.
In this course, I've made a comprehensive guide from my learnings and the industry best-practise research.
Feel free to reach out!
What will you learn?
Elevate your impact and recognition by increasing your business acumen
How to find and select the projects you and your team should be building, to provide the most value and increase your ROI
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Finding, prioritizing, and finally selecting which projects to work on is difficult to do right. You and your team is skilled, and often with a wide variety of areas you could improve with machine learning. In the course, you briefly take on the role of a product owner and learn concreate tools to get the highest ROI.
The Feedback Framework, which allows you to convincingly showcase the results you deliver and how your team impacted the organization
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Too many projects dont make it to production or are forgotten once deployed. We cover how to capture a comprehensive before and after snapshot and why production deployments are critical to get quick feedback.
You and your team are part of a larger context. Learn how to manage stakeholers and when to utilize each team member in respect of their skills.
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Time is valuable, both yours and you teams. With inspiration from CRISP-DM, we go through each phase and explore how much each role should be involved. You as a lead data scientist will be involved in most phases, but learn how and when to involve other data scientists or data engineers.
Being a Lead Data Scientist is not much different than being a data product owner. It's all about delivering results through others.
That's why this site links to our main course site for Data Product Owners - The learnings are still useful for you as a lead data scientist
Data Product Owner vs
Lead Data Scientist
Lead Data Scientist
