There are predictable challenges to be overcome when predictive models introduce change in organizations. Throughout this course, instructor Keith McCormick goes over these challenges and shows how to overcome them. Discover how to confidently defend your turf at work, enhance your own natural curiosity, deepen your commitment to your craft, effectively translate the language of analytics to the language of business, practice diplomacy, and more.
- Describe the inherent ambiguity in data science projects.
- Define cognitive empathy and how it can be acquired.
- Differentiate the roles of skepticism, curiosity, persuasion, and diplomacy in professional data science.
- List appropriate activities for continuing professional development.
- Describe common interactions between scientists and senior executives.
- Describe when it is appropriate to limit detail in discussions.
Skill Level Beginner
- If you've chosen data science as a profession you're probably quite used to working away at a tough problem alone for hours at a time. It's all part of the job. But we can't complete a whole project alone. We just can't. Data science is about addressing the challenges of organizations with data. So there are highly specific skills that help you thrive in data science that deal with how you interact and work with a variety of your colleagues, whether they be subject matter experts, or in IT, or in senior management. I'm Keith McCormick, and I've been doing these projects for 25 years now. And as I look back on dozens of projects that I've been a part of, there are definitely some lessons that I've learned. And I'd like to share them with you now.