Introduction to Data Science
What you can learn.
- Configure a data science notebook server
- Prepare a well-defined problem statement for a new problem
- Learn the R programming language
- Be introduced to machine learning
About this course:
This course introduces students to the evolving domain of data science and to the food-chain of knowledge domains involved in its application. Students learn a wide range of challenges, questions, and problems that data science helps address in different domains, including social sciences, finance, health and fitness, and entertainment. The course addresses the key knowledge domains in data science, including data development and management, machine learning and natural language processing, statistical analysis, data visualization, and inference. The course also provides an exposure to some of the technologies involved in application of data science, including Hadoop, NoSQL, and Python Programming language. The course includes case studies that require students to work on real-life data science problems.
It is advisable that you complete the following (or equivalent) since they are prerequisites for Introduction to Data Science.
Winter 2019 Schedule
These courses are fully online, and there are no in-person classroom meetings.
Enrollment limited. Enrollment deadline: January 13, 2019. Internet access required. Materials required.
These courses meet in person and make use of an online presence to varying degrees.
Enrollment limited. Enrollment deadline: January 14, 2019. Internet access required. Materials required.
Students are required to bring a laptop to class.