Major

Data Science Major

The Data Science major is a structured individual major, consisting of twelve (12) courses that include a concentration area, plus a capstone experience. Students are expected to design their major and concentration in consultation with one of the directors listed in the Major homepage and a second advisor from a department related to the concentration.

  • At least two (2) courses must be at the 300-level, and at least one of these must be from STAT or CS as opposed to the concentration.
  • A student can begin the major requirements in the first or second year. She can take MATH 115 and/or MATH 116 in their first year as prerequisites for MATH 205, if needed. Ordinarily, at least statistical modeling, data structures, and two 300-level courses must be taken at Wellesley.
The structured individual major in Data Science is large and comprehensive. Students interested in pursuing this major along with another major or minor should consult closely with both the Data Science advisors and the other department. In particular, students should not major in Data Science and minor in statistics or computer science.
 

Example Concentrations and Course Sequences

We have mapped out six possible sequences. Note that concentrations are not limited to these examples, and you are not restricted to the courses listed below if you choose one of these example concentrations.
 

Data Science with a Concentration in Economics

A concentration in Economics should include ECON 101, ECON 102, and a 200-level elective that includes discussion of empirical work. ECON 103 would count as the introductory statistics course, rather than part of the concentration. For students pursuing concentrations related to economics, ECON 203 could be one of the three electives, rather than part of the concentration.
 
  Fall      Spring
First year

(MATH 115 Calculus I)

                                   (MATH 116 Calculus II)                             

 

Second year

MATH 205 Multivariable Calculus

ECON 101 Principles of Microeconomics

  ECON 102 Principles of Macroeconomics

  CS 111 Intro to Programming

 

Third year

ECON 103 Introduction to Probability and Statistics Methods

CS 230 Data Structures

  MATH 206 Linear Algebra

  ECON 203 Econometrics

 

Fourth year

STAT 260 Applied Data Analysis

ECON 229 Women in the Economy

    STAT 309 Causal Inference

     CS 315 Data and Text Mining for the Web

 

Example Experiential Capstone: Summer internship at the Federal Reserve, Division of Research and Statistics.

 

 

Data Science with a Concentration in the Life Sciences (for example, Global Ecology or Molecular Bioinformatics)

The Life Sciences concentration should consist of either BISC 110/112 (Introductory Molecular & Cellular Biology) or BISC 111/113 (Introductory Organismal Biology) with a 200-level lab course and a 300-level lab course in the same area. BISC 198 would count as the introductory statistics course rather than as part of the concentration. Two potential pathways are highlighted below: a global ecology concentration and a molecular bioinformatics concentration.

 
  Fall Spring

 

First year

(MATH 115 Calculus I)

BISC 111/113: Introductory Organismal Biology with Lab OR

BISC 110/112: Introductory Molecular & Cellular Biology with Lab

                            

                               (MATH 116 Calculus II)                          

 

Second year

MATH 205 Multivariable Calculus

BISC 201 Ecology with Lab OR

BISC 209 Microbiology with Lab

       CS 111 Intro to Programming

       BISC 198 Statistics in the Biosciences

 

Third year

STAT 260 Applied Data Analysis

CS 230 Data Structures

       MATH 206 Linear Algebra

        CS 234 Data, Analytics, and Visualization

 

Fourth year

CS 313 Computational Biology

BISC 307 Ecosystem Ecology with Lab OR

BISC 333 Genomics and Bioinformatics with Lab

            

       STAT 228 Multivariate Data Analysis

 

Example Experiential Capstone: Senior thesis that involves analyzing large biological data sets.

 

Data Science with a Concentration in Cognitive and Behavioral Science

The Cognitive and Behavioral Science concentration offers substantial flexibility. As an illustration of the breadth of options, two example pathways are highlighted below: a clinical psychology concentration and a cognitive neuroscience concentration. PSYC 205 would count as the introductory statistics course rather than as part of the concentration.

  Fall Spring
First year

MATH 115 (Calculus I)

MATH 116 (Calculus II)

 

Second year

PSYC 101 Intro to Psychology OR

NEUR 100 Intro to Neuroscience

MATH 205 Multivariable Calculus

PSYC 205 Statistics

CS 111 Intro to Programming

 

Third year

PSYC 213 Abnormal Psychology OR

PSYC 218 Sensation & Perception

STAT 260 Applied Data Analysis

MATH 206 Linear Algebra

STAT 309 Causal Inference

 

Fourth year

CS 230 Data Structures

STAT 228 Multivariate Data Analysis

PSYC 333 Clinical and Educational Assessment OR

PSYC 314R Research Methods in Cognitive Psychology

CS 304 Databases

 

Example Experiential Capstone: Science Summer Research Program project focused on visualization tools in psychology.

 

Data Science with a Concentration in Computer Science / Data Engineering

 

  Fall Spring
First year

(MATH 115 Calculus I)

(MATH 116 Calculus II)

Second year

CS 111 Intro to Programming

MATH 205 Multivariable Calculus

CS 230 Data Structures

STAT 218 Intro to Statistics

Third Year

CS 234 Data, Analytics, and Visualization

MATH 206 Linear Algebra

CS 304 Databases

MATH/STAT 220 Probability

Fourth year

CS 240 Computer Systems

STAT 318 Regression Analysis

CS 231 Algorithms

CS 305 Machine Learning

 

Example Experiential Capstone:

QAI consulting internship, one semester, providing advice to faculty, staff, and students on projects from all across the college. We are providing this example to point out that the experiential capstone does not necessarily have to be tied to the concentration area.

 

How is this different from the CS major?

  • It requires 3 to 7 (typically 5 or 6) MATH/STAT courses (the CS major requires only two).

  • It specifies 200 and 300 electives from a subset of courses with focus on data science. CS majors can choose from a bigger set of electives (HCI, graphics, systems, etc.)

  • It drops two of the CS core components (CS 251 and CS 235), so that they are among the pool of possible concentration courses, but not required.

 

Data Science with a Concentration in Digital Humanities

Instead of ANTH/CLCV 215 or ANTH 246, students might choose to spend a summer taking CLCV/MAS 220 Digital Archaeology in Greece. Students with strong French or Spanish backgrounds might propose sequences that include digital humanities courses taught in those languages.
 
  Fall Spring
First year

(MATH 115 Calculus I)

(MATH 116 Calculus II)

Second year

MATH 205 Multivariable Calculus

STAT 101 Reasoning with Data

CS 111 Intro to Programming

MATH 206 Linear Algebra

 

Third year

STAT 260 Applied Data Analysis

ANTH/CLCV 103 Intro to Archaeology

CS 230 Data Structures

ANTH/CLCV 215 Bronze Age Greece: Archaeology and the Digital Humanities

 

Fourth year

CS 305 Machine Learning

ANTH 246 From Glyphs to Bytes: Ancient Egypt and the Future of Digital Humanities

CS 315 Data and Text Mining for the Web

STAT 228 Multivariate Data Analysis

 

Example Experiential Capstone:

One semester QAI internship focused on analysis of ancient texts, analyzing patterns in words and symbols to determine similarity of texts in one time period v. another.

 
 

 

Data Science with a Concentration in Social Justice

The concentration in social justice might also include courses from departments other than PEAC, such as economics or sociology, for students with appropriate preparation.
 
  Fall Spring
First year

(MATH 115 Calculus I)

(MATH 116 Calculus II)

Second year

CS 111 Intro to Programming

MATH 205 Multivariable Calculus

STAT 218 Intro Statistics

PEAC 104 Intro to Study of Conflict, Justice, and Peace

 

Third year

STAT 260 Applied Data Analysis

CS 230 Data Structures

MATH 206 Linear Algebra

PEAC 204 Conflict Transformation

 

Fourth year

CS 234 Data, Analytics, and Visualization

STAT 318 Regression Analysis

PEAC 358 Palestinian Israeli Peace Prospects

STAT 309 Causal Inference

 

Example Experiential Capstone: Wintersession internship at an NGO, helping to run a study to assess a program’s effectiveness.