STATISTICS ELECTIVE COURSES (MUST COMPLETE A MINIMUM OF 3 TOTAL)

*GR5293 may only count ONCE as an approved elective for the MA Program, unless approval is obtained from the academic advisor. 

**GR5398 will be counted as an elective towards graduation, only if taken for a letter grade.

PHD LEVEL COURSES IN STATISTICS

Selected PhD level statistics courses may be open to MA Statistics Students only through an application process. For more information on the process and how to apply, click HERE.

Below are electives a student might select based on interest area. These courses are recommended as a guide in course selection; however, they are not required.

Admittance into any course below is not guaranteed.  All courses are subject to availability. 

FINANCE

DATA SCIENCE SEQUENCE IN STATISTICS

*Note: The Data Science sequence includes GR5206 offered in the fall which is a prerequisite for GR5241 offered in the spring. Both courses are a prerequisite for the course, GR5242: Advanced Machine Learning.

PHARMACEUTICAL INDUSTRY OR PUBLIC HEALTH

ACTUARIAL SCIENCE AND THE INSURANCE INDUSTRY

Important: 

Biostat 6000 level courses are not approved for graduate credit in the MA Program in Statistics. 

Instructions for cross-registration:

1. Graduate students interested in taking Columbia Public Health courses must first complete the Cross-Registration Form.  

2. Obtain permission from the Public Health department(s) that offers the course(s) for which you are cross-registering. It is important to note that the process of obtaining permission to enroll in a course as a cross-registrant is approved first by the department then by the Office of Enrollment Management (OEM).  

3. Forward your completed Cross-Registration Form, as well as any other email correspondences used in lieu of signatures, to the Columbia Public Health OEM team(link sends e-mail). OEM will review and return approved forms to requesting students.   

4. If allowed to take a course, the email from OEM will include your completed and approved form(s). Complete the registration for the course through your school’s primary office for registration (gsas-studentaffairs@columbia.edu). Any change thereafter (dropping the course etc.) would also be made through GSAS.

Instructions for cross-registration:

Information about cross-registration can be found here. Questions? Email crossreg@gsb.columbia.edu

Instructions for cross-registration:

1. The IEOR department will open up select courses each semester for cross-registration on the first Friday of the semester via the SSOL course waitlist system.
2. All necessary pre-requisite requirements for the course must be satisfied.
3. A list of available courses for non-IEOR students for cross registration will be provided closer to the term start. Courses not listed are closed and/or reserved for IEOR students in a degree program.

Questions? Please contact ieor-cross-reg@columbia.edu

Important Note:  Students may take up to two courses from the list below to count toward graduation.  Students must consult with their Faculty Adviser about potential overlap in Data Science/Machine Learning courses when exploring courses not on the list below. 

Computer Science courses open to students in other departments, including Statistics students, during the Change of Program period. Enrollment is determined by the CS Department and are not guaranteed. CS course registration policy and further information can be found at: https://www.cs.columbia.edu/cs-course-registration-policy/

Non-Data Science students will be able to join a waitlist via SSOL.  Space permitting, Non-DS students will be moved from the waitlist to the class roster during the first week of classes. Questions about Data Science courses? Email DataScience-Registration@columbia.edu

Course	Course Title
U6506	Data Science & Public Policy
APMA E4990	Introduction to Data Science in Industry
BINF G4006	Translational Bioinformatics
COMS W4111	Introduction to Databases
COMS W4121	Computer Systems for Data Science (Spring course only)
COMS 4705	Natural Language Processing
COMS 4775	Causal Inference 1
COMS 4995*	Causal Inference for Data Science
COMS E 6998**	Cloud Computing & Big Data
CSOR W4231	Analysis of Algorithms I
CSOR W4246	Algorithms for Data Science
CSEE W4119	Computer Networks
ECBM E4040	Neural Networks & Deep Learning
ECBM E6040	Neural Networks and Deep Learning (Research)
EECS E6720	Bayesian Mod Machine Learning
EECS E6893	Big Data Analytics
EECS E6895	Adv. Big Data Analytics
EECS E6894	Deep Learning for Computer Vision and Natural Language Processing

*Only COMS 4995 Causal Inference for Data Science counts, other topics do not count towards graduation and require Faculty Adviser's approval. 

**Only COMS E 6998 Cloud Computing & Big Data counts, other topics do not count towards graduation and require Faculty Adviser’s approval

Please review the cross-registration information for non-MAFN students: https://www.math.columbia.edu/mafn/cross-registration-for-non-mafn-students/

APPLIED MATHEMATICS COURSE

APMA 4300 – Introduction to Numerical Methods

INAF U6506 Data Science & Public Policy – A managed waitlist will become available to MA Statistics students up to seven days before the first week of classes.  SIPA students will receive priority, but if spaces are available, MA Statistics students will be admitted.  

For courses not listed:

• The first step is to obtain the syllabus and share it with your Faculty Adviser for approval.  A Faculty Adviser may approve a course for a particular student’s schedule to count for graduation.  However, it is recommended that the faculty adviser seek input from the MA Program Faculty Directors. 
• The second step is to fill out and submit the ELECTIVES APPROVAL FORM.