Enhance your ability to ask critical questions that help your data science team make better discoveries and evaluate data. Learn about the key components of critical reasoning and how to run question meetings, organize your questions into question trees, and more.
- Renowned researcher, Jonas Salk, once said, "What people think of "as the moment of discovery is really "the discovery of the question." One of the most important parts of working in a data science team is discovering great questions. In this course, you'll see how to ask and get others to ask interesting questions of your data. To ask great questions you have to understand critical thinking. Critical thinking is not about being hostile or disapproving. It's about finding the critical questions.
These questions will help you shake out the bad assumptions and false conclusions that can keep your team from making real discoveries. In this course you'll see key components of critical reasoning, and you'll see how a to pan for gold to find new questions. Then you'll see how you can run question meetings and organize your questions into question trees. Finally, you'll see how to find new questions by challenging evidence, clarifying key terms, and uncovering misleading statistics.
This course is for anyone who's interested in being part of a data science team but isn't necessarily interested in becoming a full time data scientist. Anyone can ask critical questions, and it's often the people closest to the business that help guide the team to finding these new insights. Whether you're a long time project manager or a first year developer, this course will help you thrive on a data science team. So let's get started asking great data science questions.
- Harnessing the power of questions
- Testing your reasoning
- Identifying question types
- Organizing questions
- Rooting out assumptions
- Finding errors
- Highlighting missing data
- Overcoming question bias