Learn to hire, foster, and manage data science teams that produce deeper insights and more effective reports and visualizations.
- There is a lot of excitement around the role of a data scientist. There are university programs, new certificates, and a growing list of software and books. Mine included. It's a highly desired skill that people search for on your LinkedIn profile. Data science as a field is larger than any one role. You don't have to be a data scientist to participate in the field of data science. In fact, most organizations prefer to work in groups of highly skilled teams.
I'm Doug Rose, and in this course you’ll see how to build your data science team. I'll show you the different roles how to form a team, what each team member does, and how they work together. You’ll hear about the research lead, data analyst, and a project manager. Then you’ll see how they work as a group to ask interesting questions, run experiments, and communicate the results. The team will work with a data science mindset, they won't be afraid to disagree and they'll push for a common understanding instead of a quick consensus.
One of the biggest challenges will be making sense of the data. You’ll see strategies for group sense-making and some techniques to focus on the wholeness of the data and not the smaller parts. Instead of relying on one person who has all the skills you can build several highly skilled teams. These teams work together to produce deeper insights than you’ll usually get with any one person. So let's get started building your data science team.
Learn the holistic approach to building teams and deploying data science across disciplines. Identify the key roles and responsibilities, including research lead, data analyst, and project manager. Find out how to define areas of responsibility, foster effective communication, and build compelling reports and visualizations. Then see how to avoid the pitfalls of losing focus and arriving at false consensus. These techniques help you build highly skilled teams that produce deeper insights than you'll find from relying on data scientists alone.
- Creating a data-driven culture
- Defining team roles and areas of responsibility
- Finding wisdom in groups
- Presenting beautiful reports
- Thinking like a team
- Avoiding pitfalls