Skip to content
Data Science

Computer Science + Data Science: 3+2

Add statistical reasoning and applied modeling to your software background. The 3+2 pathway combines a Computer Science BA with an MS in Applied Data Science in a planned five years, extending your work from building software to building and evaluating systems that use data.

How the pathway fits your degree

Choose Python, Calculus I and Linear Algebra within the AOC; add Probability I.

Calculus I
Use one of the two math/statistics elective slots.
Introduction to Programming in Python
Select Python for the introductory programming requirement.
Probability I (one module)
The sample uses the two math slots for Calculus I and Linear Algebra.
Linear Algebra
Use the second math/statistics elective slot.

Applications in Computer Science

Data engineering

Design a pipeline that validates, stores and prepares data for analysis.

Machine learning systems

Connect a trained model to an application and evaluate how well it performs.

Product and system data

Use logs or usage data to investigate performance, behavior and reliability.

Plan your undergraduate work

Coursework

Keep the core programming sequence and the five advanced-elective categories in view. Plan math choices before filling both elective slots.

Practical capstone

The CS internship, community software project or REU is a separate AOC requirement. Schedule it before BA completion; the Year 5 MS practicum comes later.

Related subjects

Your CS electives may overlap with graduate databases, programming or machine learning. Review the content with both advisors before selecting them.

These are sample schedules. Work with your area-of-concentration sponsor to confirm course prerequisites, actual offerings, remaining BA requirements and the fall thesis deadline. Graduate courses do not automatically replace undergraduate requirements.

Sample course schedule: Years 1–5

Each course or thesis activity appears on its own line. General-education choices are examples to review with your sponsor.

Year 1 fall

Undergraduate

  • Introduction to Programming in Python
  • Calculus I
  • English Composition
  • Homer's Odyssey: Introduction to Humanities

Year 1 spring

Undergraduate

  • Object Oriented Programming
  • Discrete Mathematics
  • Calculus II
  • Introduction to Techne

Year 2 fall

Undergraduate

  • Object Oriented Design
  • Data Structures
  • Linear Algebra
  • Foundations of Biology I

Year 2 spring

Undergraduate

  • Algorithms
  • Introduction to Programming in C (languages elective)
  • Probability I
  • American Government and Civics

Year 3 fall

Undergraduate

  • Software Engineering
  • Foundations of Human Centered Computing (applications)
  • Introduction to Literature (general-education choice)

Graduate

  • IDC 5204 Applied Statistics I
  • IDC 5110 Data Munging and Exploratory Data Analysis

Year 3 spring

Undergraduate

  • Artificial Intelligence (AI)
  • Computer Systems, Architecture and Digital Hardware (systems)
  • Introduction to Political Theory (general-education choice)
  • Introduction to Poetry (general-education choice)
  • CS thesis research tutorial: prototype and evaluation

Year 4 fall

Undergraduate

  • Theory of Computation (theory)
  • Classical Mythology (general-education choice)
  • CS thesis writing, final software and BACC

Graduate

  • IDC 5120 Programming for Data Science
  • IDC 5130 Databases for Data Science

Year 4 January

Graduate

  • IDC 5295 Industrial Workshops (non-credit)

Year 4 spring

Graduate

  • IDC 5205 Applied Statistics II
  • IDC 5112 Communications and Applied Domains in Data Science
  • IDC 5210 Applied Machine Learning
  • IDC 5131 Distributed Computing

Year 5 fall

Graduate

  • IDC 6200 Advanced Statistical Modeling
  • IDC 6215 Deep Learning and AI
  • IDC 6250 Practical Data Science

Year 5 spring

Graduate

  • IDC 6294 Industrial Practicum II

The MS requires 36 graduate credits. Complete the BA credit, general-education and area-of-concentration requirements as well.

Thesis, BACC and independent study

Plan three January Independent Study Projects (ISPs) during Years 1–3, including the projects required by your area of concentration. Use this work to prepare for your senior thesis.

Develop the thesis with your sponsor during Year 3. The original 3+2 plan calls for completing the thesis, Baccalaureate Exam (BACC) and all remaining BA requirements in Year 4 fall, before formal graduate entry in spring.

If thesis timing changes, discuss a revised course and graduation plan with the program director. The original plan places formal graduate admission in the first spring after all BA requirements are complete.

Sample January projects

  1. Year 1: Python programming project
  2. Year 2: software design project
  3. Year 3: thesis pilot and evaluation plan

In the summer after Year 3, complete your technical internship, community software project or Research Experience for Undergraduates (REU). This is a separate Computer Science requirement.

Advising and references

For help planning your pathway, contact graduateDS@ncf.edu.

3+2 overview →Graduate course descriptions →Apply for the pathway →

References: NCF 3+2 pathway; original program proposal (PDF).