How can we use data for social impact? In this introductory course, students learn foundational theory and the coding skills necessary to translate data into actionable insights. Students learn about some of the latest tools and algorithms being used by corporate and academic machine learning teams (e.g. Google, Uber, Facebook, Udemy, Stitch Fix, Amazon and Apple). Each of the 6 hands-on, project-based modules use real world data from KIVA, a non-profit that connects people through lending to alleviate poverty. Data is powerful, and we believe that anyone can harness it for change.
Data science is a highly interdisciplinary practice, demanding critical thinking, understanding of statistics, and technical coding ability. Irresponsible application of powerful algorithms or an inadequate exploration of underlying assumptions can lead to spurious results. In this course, we emphasize the fundamentals of proper data science and expose students to what is possible using sophisticated machine learning methods.
Follow our curriculum development on our Github.
Data science is a highly interdisciplinary practice, demanding critical thinking, understanding of statistics, and technical coding ability. Irresponsible application of powerful algorithms or an inadequate exploration of underlying assumptions can lead to spurious results. In this course, we emphasize the fundamentals of proper data science and expose students to what is possible using sophisticated machine learning methods.
Follow our curriculum development on our Github.
