Postgraduate Course: Introduction to Research in Data Science (INFR11138)

Course Outline
School	School of Informatics	College	College of Science and Engineering
Credit level (Normal year taken)	SCQF Level 11 (Postgraduate)	Availability	Not available to visiting students
SCQF Credits	20	ECTS Credits	10
Summary	This course provides students with an overview of current research topics in data science. This overview is provided by guest lectures from researchers working throughout different areas of data science, including databases, machine learning, maths, natural language processing, computer vision, speech processing, and related areas. Second, this course also features a small project to provide students with experience in applying data science methods. The goal of the project is to apply an existing data science method to a interesting real or realistic problem. The student will produce a short project report and poster presentation based on the project.
Course description	This course provides students with an overview of current research topics in data science. This overview is provided by guest lectures from researchers working throughout different areas of data science, including databases, machine learning, maths, natural language processing, computer vision, speech processing, and related areas. Second, this course also features a small project to provide students with experience in applying data science methods. The goal of the project is to apply an existing data science method to a interesting real or realistic problem. The student will produce a short project report and poster presentation based on the project.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites		Co-requisites
Prohibited Combinations		Other requirements	None

Course Delivery Information

Academic year 2017/18, Not available to visiting students (SS1)		Quota: None
Course Start	Semester 1
Timetable	Timetable
Learning and Teaching activities (Further Info)	Total Hours: 200 ( Lecture Hours 18, Seminar/Tutorial Hours 12, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 166 )
Assessment (Further Info)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Feedback	Not entered
No Exam Information

Learning Outcomes
On completion of this course, the student will be able to: Be able to identify current research issues and trends in data science. Gain increased fluency with main ideas and concepts across the different disciplines that make up data science. Gain experience in applying data science methods in practice. Develop skills in report writing and presentation writing.