Course Schedule - Spring Semester 2018

     

COMP 543 001 (CRN: 25317)

GR TOOLS & MODELS - DATA SCI

Long Title: GRADUATE TOOLS AND MODELS - DATA SCIENCE
Department: Computer Science
Instructors:
Myers, Risa B.
Jermaine, Christopher M.
Meeting: 1:00PM - 1:50PM MWF DCH 1075 (8-JAN-2018 - 20-APR-2018) 
Session: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
 
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 0 (permission required) Instructor Permission Required
Section Enrolled: 16
Enrollment data as of: 2-APR-2020 4:45AM
 
Fees: None
 
Final Exam: GR Course-Dept Schedules Exam
 
Description: This course is an introduction to modern data science. Data science is the study of how to extract actionable, non-trivial knowledge from data. The course will focus on the software tools used by practitioners of modern data science, the mathematical and statistical models that are employed in conjunction with such software tools and the applications of these tools and systems to different problems and domains. On the tools side, we will cover the basics of relational database systems, as well as modern systems for manipulating large data sets such as Hadoop MapReduce, Apache Spark, and Google’s TensorFlow. On the model side, the course will cover standard supervised and unsupervised models for data analysis and pattern discovery. Mathematical sophistication (calculus, statistics) and programming skills that would be acquired in an undergraduate computer science program are expected. Most programming will be in Python and SQL. (SQL is covered in the course) with some Java. Mutually Exclusive: Cannot register for COMP 543 if student has credit for COMP 330.