Based on our experience with online learning and the feedback from round 1, we’re actively designing and maintaining material to encourage diversity in ideas and audience. In practice this means:
- We are focussed on the practical: for programming to be useful it needs to be practical, with benefits that can be applied to your work. Reflecting this, our material is intentionally focussed on helping you learn what you need to know while not overwhelming you with unnecessary detail.
- We believe good public policy and good programming is multidisciplinary and diverse: the world is complex, diverse and changes fast. Good public policy development recognizes this by drawing on the ideas and experiences of diverse people from across the community. Our material reflects this by seeking insights, ideas and applications from as diverse a range of people, academic disciplines and industries as we can (no manels!).
- We believe in using data for good: as access to data multiplies so too can our opportunities to make the world a better place, provided we have access to the right tools and knowledge. We believe programming represents a critical part of these tools. The course is therefore designed to demonstrate this by using real-world datasets and examples that demonstrate how data science can make the world a better place.
- We think learning programming should be fun and done with friends: Sure, we’re nerds. But chances are, you are too! Which is great, as learning how to do data science is best done with friends. Our material reflects this, with active efforts to link you up with others that share your interests and drive you to learn how to program.