Minor and concentrations

Explore the expanding realm of data science with our Data Science Minor and specialized concentrations in Business Data Analytics (BDA) and Geospatial Data Analytics (GDA), designed to complement any major.

Clark offers a large variety of academic programs and supports students to pursue their interests through combinations of majors and minors in their chosen fields. Furthermore, our student clubs and growing data science alumni community provide enrichment activities, mentoring and networking opportunities.

The Data Science Minor equips you with foundational knowledge and practical skills that are crucial in today’s data-driven world. The BDA concentration focuses on the application of data science in business contexts, preparing you to make data-driven decisions that propel business strategies forward. The GDA concentration offers you the opportunity to delve into spatial data analysis, opening doors to careers in urban planning, environmental science, and beyond. Whether you aim to integrate cutting-edge data analysis techniques into your primary field of study or seek to enhance your career prospects, these programs provide the knowledge and skills that will help you stand out among your peers and position you for future success.

Our interdisciplinary approach not only ensures that students gain a deep understanding of both theoretical and practical aspects but also fosters collaboration among faculty and student across various disciplines. Whether your interest lies in pursuing graduate studies or applying data science to fields such as health informatics, financial analytics, or environmental science, our program paves the way for you to become a proficient and insightful data science professional.

Apply

Visit

Request more info

Explore concentrations

The Data Science program at Clark University offers minor concentration which is designed to complement a variety of major fields, equipping students with valuable skills in data analysis, statistical modeling, and computational thinking.

Geospatial Data Analytics

The Concentration in Geospatial Data Analytics is designed to equip students with the skills and knowledge needed to analyze and interpret geospatial data effectively.

Business Data Analytics

Business Data Analytics is a concentration that combines foundational quantitative and analytics skills, programming knowledge, and business and economics applications.

Explore core and foundational courses

Clark University’s Data Science program include statistical analysis, machine learning, data visualization, and programming. These foundational classes ensure students develop essential skills to tackle real-world data challenges effectively.

Data Science core courses

DSCI 105 – Applied Data Analytics

An investigation into the fundamental techniques and practices of data analysis, this course focuses on applying tools and techniques to practical problems of analysis, visualization, and discovery.

caulk board with mathematical foundations written on it

DSCI 122 – Mathematical Foundations of Data Science

This course provides an introduction to the key mathematical principles underlying data science. The course focuses on linear algebra, probability, statistics, and calculus, as these areas are crucial for understanding.

DSCI 125 – Introduction to Data Science

This course provides foundational knowledge in statistical and computational concepts essential for data-centered computing and its applications.

earth at night with lights shining in major areas.

DSCI 215 – Applying Deep Learning to Earth Observation

Applying Deep Learning to Earth Observation delves into the application of deep learning techniques to analyze and interpret data from Earth observation systems.

DSCI 216 – Stochastic Computing

Stochastic Computing focuses on addressing the uncertainty inherent in data science and computer science through a combination of problem analysis, theoretical development, and prototype creation.

DSCI 225 – Applied Machine Learning

Applied Machine Learning explores the fundamental techniques and practices of machine learning through a series of lectures, lab sessions, programming projects, and written assignments.

Computer Science core courses

CSCI 120 – Introduction to Computing

Introduction to Computing is a foundational course designed to develop computational problem-solving skills through programming while introducing students to various essential topics in computer science.

man behind clear board with drawings on it

CSCI 121 – Data Structures

Data Structures provides a comprehensive introduction to the fundamental data structures used in computer science. The course covers a range of data structures including arrays, linked lists, stacks, queues, trees, and graphs.

CSCI 124 – Honors Introduction to Computing

Honors Introduction to Computing is an accelerated course that provides a comprehensive introduction to computing and its diverse applications.

Mathematics core courses

MATH 120/MATH 124 (Calculus I)

Calculus I is often the first course in a standard calculus sequence and typically covers topics such as limits,derivatives, and integrals. It is a foundational course for understanding calculus.

MATH 121/MATH 125 (Calculus II)

Calculus II, typically referred to as MATH 121, is the second course in a standard calculus sequence. It builds upon the concepts introduced in Calculus I, such as limits, derivatives, and integrals, and dives deeper into their applications and extensions.

Data Science