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.
Course OutlineThis course introduces students to the evolving domain of data science and the foodchain of knowledge domains involved in its application. Students learn a range of challenges and questions that data science helps address.
PrerequisitesThere are no prerequisites for this course, although students should be comfortable using computer software programs. Prior training/experience in mathematics and statistics is helpful. Similarly, knowledge of programming and of a programming language is beneficial. Thinking out of the box and a curious mind are the key traits of a successful data scientist.
Applies Towards the Following Certificates
- Applications Programming : Electives
- Applications Programming in C# .NET : Electives
- Business Analysis : Defined Elective - Electives
- Data Science : Required
- Database Management : Electives
- Linux/Unix : Electives
- Operating System Administration : Electives
- Study Abroad at UCLA Program : Required
- Systems Analysis : Electives
- Web Technology : Electives