Advanced D2K Courses:
DSCI 400, Data Science Capstone Lab
Instructor: Arko Barman
Description: In this project-based course, student teams will choose, define, and execute semester-long data-science and machine-learning research projects. These projects may be selected from a variety of disciplines and industries, where freedom is given in defining the projects. The course is about learning best practices in data science and machine learning while finding a suitable curiosity-driven project to build these methods and systems around.
Intended for DSCI minor students and non-seniors who have some background in data science and want to learn how to design a data science pipeline to answer questions and tell a story through data.
Prerequisites: (DSCI 301 OR STAT 315 OR STAT 310 OR ECON 307) AND (DSCI 302 OR COMP 330) AND (DSCI 303 OR STAT 413 OR COMP 540) AND DSCI 304
Course Meeting: 1:30 PM - 2:50 PM Tuesdays & Thursdays
DSCI 435 / 535 & COMP 449 / 549, Applied Machine Learning & Data Science Projects
Instructors: Genevera Allen, Su Chen and Arko Barman
Description: In this course, students will work on interdisciplinary teams to solve a real-world data science project with clients from a variety of industries and disciplines.
Intended for seniors (some advanced juniors), professional masters, and beginning PhD students who have advanced coursework and expertise in some area of data science and want to complete a challenging, real-world data science project.
Counts as the Data Science minor capstone, the MDS capstone, an elective capstone for Stat seniors, CAAM seniors, and MECE students as well as an elective for ELEC, COMP, STAT and CAAM undergrads and grads.
We anticipate having about 15 projects in the fall. These are industry-sponsored (finance, energy, healthcare, tech), community impact projects (government and non-profits), and research projects (working with Rice or medical center faculty).
You can register for the course now and a course application and project preference form will be due the first week of classes to determine projects and teams. Students who do not meet the course prerequisites may be asked to enroll in DSCI 400.
Course Meeting: 5:00 PM - 6:30 PM on Mondays & Wednesdays
Intro-Level D2K Courses:
DSCI 101: Introduction to Data Science (NEW)
Instructor: Su Chen
Description: Students learn the fundamentals of data science and Python programming while working on teams to solve real data science challenges, design a data science pipeline, and derive and communicate valuable insights from data.
Intended for undergrads and no prior statistics, math, or programming experience is required.
Gain fluency in basic programming skills in Python with a focus on statistical modeling and machine learning.
Prerequisites: No prior background in statistics or programming required.
Course Meeting: 9:45 AM - 10:40 AM on Mondays, Wednesdays and Fridays
Contact the course instructors or email email@example.com with any inquiries.
View student projects from the previous year: