Admission Requirements

To view application requirements for general admission, click here.
Penn Engineering master’s students interested in transferring to the Data Science Program can only apply after the end of their first semester at Penn, and no later than the add/drop deadline of their third semester.
Requirements for Penn Engineering master’s students transferring to the Data Science Program include:

• Completed the two foundations courses (Probability and Programming) with a grade of A- or better either as an undergraduate or at Penn as a graduate student via the following courses:

1. Probability (Intro to Probability & Statistics ENM 503 or  Probability STAT 510 or Advanced Probability MATH 546)

2. Programming (Programming Languages & Techniques CIT 590 or Introduction to Software Development CIT 591)

• Completed Big Data Analytics CIS 545 or Introduction to Machine Learning CIS 519 with a grade of at least A

The Admissions Committee will also consider any additional background the applicant has in math (e.g. linear algebra, mathematical modeling, optimization) and programming.

Transfer requests will not be considered until after grades have been posted for courses taken during the first semester of the applicant’s original Master’s program.

Requests are evaluated using the same criteria for candidates applying directly to the Data Science Program, i.e. candidates should have the same course background, academic credentials, test scores, etc.

Click here to access School of Engineering information regarding transferring programs.

Additional Application Requirement

The Personal Statement must clearly explain why the candidate wishes to transfer into the Data Science Program and how their background prepares them.
Penn engineering master's students interested in pursuing a dual degree with the Data Science Program can only apply after the end of their first semester at Penn, and no later than the add/drop deadline of their third semester.

Due to the overlap in programs, dual degree applications with CIS/CIT/SCMP are strongly discouraged.

Requirements for Penn Engineering master’s students interested in pursuing a dual degree with the Data Science Program include:

• Completed the two foundations courses (Probability and Programming) with a grade of A- or better either as an undergraduate or at Penn as a graduate student via the following courses:

1. Probability (Intro to Probability & Statistics ENM 503 or  Probability STAT 510 or Advanced Probability MATH 546)

2. Programming (Programming Languages & Techniques CIT 590 or Introduction to Software Development CIT 591)

• Completed Big Data Analytics CIS 545 or Introduction to Machine Learning CIS 519 with a grade of at least A

The Admissions Committee will also consider any additional background the applicant has in math (e.g. linear algebra, mathematical modeling, optimization) and programming.

Dual degree requests will not be considered until after grades have been posted for courses taken during the first semester of the applicant’s original Master’s program.

Requests are evaluated using the same criteria for candidates applying directly to the Data Science Program, i.e. candidates should have the same course background, academic credentials, test scores, etc.

Click here to access School of Engineering information regarding dual degree programs.

Additional Application Requirement

The Personal Statement must clearly explain why the candidate wishes to pursue a dual degree with the Data Science Program and how their background prepares them.
Penn undergraduate students should not apply for submatriculation status in the Data Science Program until their junior year. Qualified undergraduates from any Penn school, subject to their home school's rules and regulations, are eligible to apply.
Requirements for Penn undergraduate students applying for submatriculation status in the Data Science Program:

• Minimum major GPA of 3.2

• At least a B+ in the following courses:
1. Programming Languages and Techniques CIS 120

2. Probability (ESE 301 or STAT 430)

3. A Data Science Course (CIS 545 or ESE 305) or a Machine Learning Course ( CIS 419/519, CIS 520, ESE 545 or STAT 471 )

The Admissions Committee will also consider any additional background the applicant has in math (e.g. linear algebra, mathematical modeling, optimization) and programming.

Admissions decisions are made only after the above mentioned three courses are completed. Admission is selective and decisions are made by the graduate group.

Click here to access the School of Engineering Information regarding the submatriculation option.

Additional Application Requirement

The Personal Statement must clearly explain why the candidate wishes to submatriculate into the Data Science Program and how their background prepares them.