Where do I start?

Welcome to MSCS! We offer courses in computer science, data science, mathematics and statistics.

There are several starting points in the department curriculum. If you are unsure of your area of study, don’t worry! Our entry-level courses are great opportunities to explore the four disciplines and often count towards multiple MSCS majors. 

Students come to Macalester with a wide variety of previous experience. Depending on student background, the most common starting courses are:

  • Computer Science: Comp 120 or Comp 123, Comp 127
  • Data Science: Stat/Comp 112
  • Mathematics: Math 135, Math 137, Math 237, Math 279
  • Statistics: Stat 155

The sections below offer detailed information and advice about course placement, based on the courses that you’ve already taken.

Interested in transferring credits for an AP exam, an IB Exam or a college course that you’ve taken elsewhere? That’s a separate process. Please check out the Macalester Registrar’s AP/IB Policy and their Transfer FAQ.

Starting Points in Computer Science

If you are interested in a Computer Science major, consider taking an entry-level computer science course (Comp 123 or Comp 127). Also consider taking Discrete Mathematics (Math 279).

Comp 120/Comp 123: Two introductory courses assume no previous experience with programming.

  • Comp 120, Computing and Society, is offered occasionally, usually as a first-year course. It serves as an alternative to Comp 123. Course Description.
  • Comp 123, Core Concepts in Computer Science is the most common starting point in our Computer Science curriculum, and is offered every semester. Course Description

Both courses are suitable for students with little or no background in computing, programming, or computer science.  These courses serve as a first course in the major and minor as well as an introduction to computer science for those not planning to take further coursework.

Comp 127: Object-Oriented Programming and Abstraction: Students who have significant prior experience in computer science, like a strong programming course or the APCS course, may choose to start in Comp 127 with permission of the instructor. Course Description.

Students who are uncertain which course to enroll in should contact the chair of Computer Science for advice.

Starting Points in Data Science

If you are interested in a Data Science major, consider taking Stat/Comp 112. Also consider exploring entry-level courses in computer science, statistics, and mathematics as the major includes components of all three disciplines.

Stat / Comp  112: Introduction to Data Science This course provides an introduction to the handling, analysis, and interpretation of the big datasets and assumes no experience with programming.  It is required for the Data Science major and minor. It counts as a computational course for the Statistics major/minor. It counts for the Math major as a supporting class. This serves as a good first course to the major and minor as well as an introduction to for those not planning to take further coursework. Course Description.

Starting Points in Mathematics

If you are interested in a Mathematics major, consider taking a course in the Applied Multivariable Calculus sequence (Math 135, Math 137, Math 237), or Math 279 Discrete Mathematics. Also, consider entry-level courses in Computer Science and Statistics. Usually, we advise students to wait to take Math 236 Linear Algebra until they’ve taken at least one other MSCS course at Macalester.

Calculus Sequence

The material in our three-course calculus sequence AMC I, II, III is organized differently than the traditional Calculus I, II, III sequence found at most colleges and universities. In particular, all three of our courses use functions of multiple variables, and emphasize applications. But student placement is compatible with traditional Calculus courses.

This workflow diagram illustrates calculus placement based upon previous calculus experience. But there are other important factors in choosing a course, including your academic goals, your confidence level, and the intensity of your other commitments. You might be unsure about where to start (which is very common). If you want some advice, then please fill out this very short survey about your math background. You’ll hear from a mathematics faculty member soon after. 

 

Math 135, Applied Multivariable Calculus I: This course is designed for students with no calculus background. It is also recommended for students with a calculus background who want to strengthen their fundamental calculus skills and while also developing mathematical modeling skills. Course Description.

Math 137, Applied Multivariable Calculus II: This course is recommended for students who feel comfortable with derivatives and have had a successful year of high school calculus (for example, AP Calculus AB with a score of 4 or 5; IB HL Mathematics: Analysis and Approaches with a score of 5;  IB HL Mathematics: Applications and Interpretations with a score of 6 or 7). Course Description.

Math 237, Applied Multivariable Calculus III: This course is recommended for students who have had two successful years of high school calculus and are comfortable with both derivatives and integrals (for example, AP Calculus BC with a score of 4 or 5; IB HL Mathematics: Analysis and Approaches with a score of 6 or 7). Course Description.

Other starting points in Mathematics

Math 279: Discrete Mathematics is an excellent starting point for students who are interested in mathematics and want to try out areas of mathematics other than calculus. This course is required for the Computer Science major and can count towards the Mathematics major. Course Description.

Math 236: Linear Algebra  is a good starting point for students who have already completed calculus at the level of Math 237 or taken a proof-based mathematics course (like Math 279). For other students, we recommend that you wait to take Math 236 Linear Algebra until after you have at least one other MSCS course at Macalester. This course is required for the Data Science major, the Mathematics major, and the Statistics major. Course Description.

Starting Points in Statistics

If you are interested in a Statistics major, consider Stat/Comp 112 or Stat 155. Also consider the calculus sequence (up to Math 137) or an entry-level computer science course.

Stat / Comp  112: Introduction to Data Science This course provides an introduction to the handling, analysis, and interpretation of data and assumes no experience with programming.  It is required for the Data Science major and minor. It counts as a computational course for the Statistics major/minor and as a supporting class for the Math major. This serves as a good first course to the major and minor as well as an introduction to for those not planning to take further coursework. Course Description.

Stat 155: Introduction to Statistical Modeling is our introductory statistics course.  It is required for the Data Science major and minor, the Statistics major and minor, and other majors on campus (including Biology and Economics). It also counts for the Math and Computer Science majors as a supporting class. Stat 155 is a course unique to Macalester, with an emphasis on multivariate modeling, and it cannot be replaced by AP Statistics credits. Course Description.

MSCS Courses Required by Other Programs of Study

Some programs of study require MSCS courses. Contact the home department with questions about how these courses fit into those majors. Below are some programs outside MSCS and their course requirements.

  • Biology major: requires Stat 155.
  • Chemistry major: requires calculus through Math 137, and Math 236.
  • Community and Global Health concentration: requires Stat 125.
  • Economics major: requires Stat 155 and one of Math 135, Math 137 (recommended) or Math 237. 
  • Pre-Health students: all should take Stat 155 and some should take calculus. Contact the Health Professions Advising Committee for guidance tailored to your interests and plans.
  • Physics major: requires calculus through Math 237, and recommends Math 236 and Math 312.