Program of Study

The ten course units for the Data Science degree are divided into three categories:

(As long as the prerequisites for the courses are met, students can complete these courses in any sequence.  Rules that Accelerated Masters students should abide by are listed here. Accelerated Masters students should ensure that they only enroll for graduate versions of courses once they matriculate in the DATS program.)

Students who matriculated in Fall 2020 and earlier can follow the DATS curriculum (entered Fall 2019 or later) OR the most current curriculum below.  As a result of the ongoing reviews of the program, certain course offerings, program requirements, and course prerequisites are subject to change without notice. Where a change in program requirements is made while a student is enrolled, the student may elect to complete the program under the requirements in effect at the time of matriculation.


1.  Foundations (two course units)

  • Programming Languages & Techniques (PL): Programming Languages & Techniques (CIT 5900) or Introduction to  Software Development (CIT 5910) 
  • Linear Algebra (CIS 5150) OR Computational Linear Algebra (Math 5130)

If students have taken these courses as part of another program, the requirement may be waived. 

For Accelerated Masters,  the programming requirement can be waived with successful completion of a B+ or higher in CIS 1200. The linear algebra requirement can be waived with a B+ or higher in Math 3120. The Stats requirement can be waived with a B+ or higher in Stat 4310. A student may also waive Foundation requirements with any other relevant course after getting department approval.  

Please understand that CIS 1200, Math 3120, Stat 4310 or any other relevant undergraduate course can only be used to waive these requirements and CAN NOT be used as courses to count towards the master’s degree. Upon waiving these requirements, students must take Technical Electives or a course of their choice (subject to department approval) in lieu of them. 


2. Core Requirements (three course units)

  • Statistics for Data Science (ESE 5420)
  • Big Data Analytics: Big Data Analytics (CIS 5450)
  • Mining and Learning: Intro to Machine Learning (CIS 5190) or Machine Learning (CIS 5200) or Modern Data Mining (STAT 5710) or  Data-driven Modeling and Probabilistic Scientific Computing (ENM 5310) or Data Mining: Learning from Massive Datasets (ESE 5450)

3. Technical & Depth Area Electives (five course units)

Students must choose courses from at least 3 of the buckets listed below. 

BUCKETS for Technical & Depth Area Electives

Applications

Register for two credits of DATS 597/Master’s Thesis or two credits of DATS 599/Master’s Independent Study. Suggestions for projects will be provided to students. Students may choose from these suggested projects or may also come up with their own project/advisor ideas. Students will be mentored jointly by the Program Director and by an advisor in the area of the project, and must receive approval by Faculty Director.
  • Brain-Computer Interfaces (BE 5210)
  • Network Neuroscience (BE 5660)
  • Intro to Biomedical and Health Informatics (BMIN 52100)
  • Introduction to Computational Biology and Biological Modeling (CIS 5360)
  • Biomedical Image Analysis (CIS 5370)
  • Theoretical and Computational Neuroscience (PHYS 5850)
  • Ethical Algorithm Design (CIS 5230) 
  • Econometrics I- Fundamentals (ECON 7050) 
  •  Econometrics III: Advanced Techniques of Cross-Section Econometrics (ECON 7210)
  •  Econometrics IV: Advanced Techniques of Time-Series Econometrics (ECON 7220)
  •  Applied Probability Models in Marketing (MKTG 7760)

Methods

  • Data and Analysis for Marketing Decisions (MKTG 7120)
  • Business Analytics (OIDD 6120)
  • Forecasting Methods for Management (STAT 5350)
  • Accelerated Regression Analysis (STAT 6210) (limited to MBA students only)
  • Predictive Analytics for Business (STAT 7220)
  • Sample Survey Methods (STAT 9200)
  • Observational Studies (STAT 9210)
  • Modern Regression for the Social, Behavioral and Biological Science (STAT 9740
  • Molecular Modeling and Simulations (CBE 5250
  • Computational Science of Energy and Chemical Transformations (CBE 5440)
  • Multi Modeling of Biological Systems (CBE 5590)
  • Finite Element Analysis (MEAM 5270
  • Computational Mechanics (MEAM 6460)
  • Atomic Modeling in Materials Science (MSE 5610

Information re: Data Science (DATS) Minor can be accessed here


More Information

  • Information re: Computer & Information Science courses and faculty can be accessed here
  • Information re: Statistics courses and faculty can be accessed here
  • Information re: Electrical & Systems Engineering courses and faculty can be accessed here
  • Information re: Bio engineering courses and faculty can be accessed here
  • Information re: Physics courses and faculty can be accessed here
  • Information re: Economics courses and faculty can be accessed here
  • Information re: Marketing courses and faculty can be accessed here
  • Information re: all courses offered at the University of Pennsylvania can be accessed here