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Product Mentality for Data Scientists and Engineers

Category: Tutorials

Product Mentality for Data Scientists and Engineers
Published 05/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 7 lectures (3h 22m) | Size: 874.1 MB

Making Data Scientists and Engineers a successful part of the product team
What you'll learn
Key terms and concepts for product, product management and product development.
How to identify and mitigate risks for product development.
How to be a better member of any product team.
How to identify and avoid anti-patterns on product teams.
How to gain and apply a product mentality.
The differences between outcomes, outputs and opportunities.
The differences between metrics, KPIs and OKRs.
No prerequisites are needed.
This course offers targeted and impactful material to help Data Scientists and Engineers who are currently, or will be working on product teams. Having the right information, the more technical roles on a product team can help ensure the work they are doing is contributing to a successful product that users and customers actually want. As more products contain Machine Learning, Artificial Intelligence and Data Science capabilities, Product Managers and Data Scientists/Engineers will be working more closely together. Having a common understanding of core concepts and thinking about product in the same way, these roles can be mutually beneficial. Demonstrating a good understanding of product management fundamentals will also help Data Scientists and Engineers in their professional career.
After taking this course, you will be able to demystify product management concepts and have the tools needed to be identify product risk, identify opportunities for developing and improving products, and identify common anti-patterns and how to correct them. Key terms that are used frequently by product managers and stakeholders are also covered, and learners of this course will learn about objective key results (OKRs), key performance indicators (KPIs) and their relationship to model metrics that Data Scientists are familiar with.
The material in this course is based on my professional experience and personal interest in product management. By learning the key concepts of product management and maintaining a product mentality, products and projects have a better chance of success in a very competitive marketplace. At the end of the course, I will share my thoughts on several rules of success, which should be helpful for learners in their professional future.
Who this course is for
Data Scientists, Analysts, Machine Learning Engineers and other Engineers that work on product teams.
Anybody interested in product management.
Lead data scientists and engineers.
Product team members that deliver software products with data scientists or data science capabilities.


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