Data Science, BSDS

The Data Science degree is a gateway to mastering the language of the future by equipping you with the analytical skills to tackle real-world problems. Data science is one of the fastest-growing fields with a high demand for skilled professionals across various industries. Specialize in areas of interest through electives and practical experience as you develop sought-after skills in the workforce.

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Program Overview

The Data Science degree offers training in data analysis, preparing students for diverse careers in various sectors such as healthcare, finance, and education. This interdisciplinary program focuses on teaching you how to convert raw data into meaningful insights using advanced techniques like data mining and machine learning.

As a data science student, you will develop the ability to build and assess data-based models as well as skills in data wrangling and data management. Learn how to visualize, conceptualize data, and extract meaning for relevant audiences while cultivating an understanding of the ethical and privacy aspects of data in different contexts.

Concentrations

The College of Emerging and Collaborative Studies offers five concentrations that allow learners to deepen their knowledge and skills in their specific area of interest.

Applied Computing – The Applied Computing concentration (12 credit hours) is designed to provide students with a strong foundation in key computing concepts, preparing them for careers in a variety of industries.
Bioinformatics – The Bioinformatics concentration (12 credit hours) is intended to equip students with bioinformatics knowledge and skills necessary in a range of settings, including post-graduate studies and work in industry, research institutions, and some government agencies.
Leadership Studies – The Leadership Studies concentration (12 credit hours) is designed to provide students with the opportunity to build foundational knowledge in leadership theory, strengthen leadership skills, and develop leadership capacity through experiential and applied learning opportunities.
Sport Analytics – The Sport Analytics concentration (12 credit hours) provides students and learners with foundational skills and best practices for applied sport data analytics. The curriculum is designed to align with the current demands and trends in the sport analytics industry.
Technical Communication – The Technical Communication concentration (12 credit hours) is designed to prepare students to effectively convey complex technical information to diverse audiences using industry-standard tools and best practices.

Why study Data Science

Data Science Is In Demand

Data science is one of the fastest-growing fields with employment projected to grow by 35% between 2022-2032.

Hands-On Learning

CECS partners with industry to provide students with real-world experience in data science through internships, co-ops, capstones, and research projects.

Specialize Your Interests

The flexibility and interdisciplinary nature of the CECS data science degree gives students the opportunity to specialize their studies to align with their interests.

Career Opportunities

According to the Bureau of Labor Statistics, Data Science employment is projected to grow by 35% between 2022-2032, demonstrating the demand for Data Science Majors.

Competitive Salaries

The median salary for a Data Science professional is $108,020 as of May 2023. 55% of Data Science roles are entry-level across a variety of sectors.

Transferrable Skills

In 2022, the most popular fields of work for data scientists were computer system design, insurance, management of enterprises, technical consulting, and research.

What can you do with a Data Science degree after graduation?

Careers paths for a Data Science major are almost limitless! Data Scientists are needed across sectors like finance, marketing, research, sports, and healthcare to cultivate and analyze data and use that data to drive decision making. Here are just a few career opportunities for a Data Science Major.

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Data Analyst

A data analyst collects, cleans, and analyzes data to identify patterns and insights that help organizations make informed decisions. They create visualizations and reports to communicate findings and provide actionable recommendations to stakeholders.

Market Researcher

A market analyst studies market conditions to assess potential opportunities, gathering and analyzing data on consumers, competitors, and market trends. They provide insights and forecasts to help develop marketing strategies and make informed decisions.

Data Architect

A data architect designs and manages an organization’s data infrastructure, ensuring data is stored, integrated, and accessible efficiently and securely. They develop data models and establish standards for data management.

Sports Analyst

A sports analyst evaluates the performance and strategies of athletes and teams by analyzing game statistics, player data, and historical trends. They provide insights and predictions to inform coaching decisions, team strategies, and media commentary.

Featured Courses

Data Science courses are comprehensive and hands-on, equipping students with the skills required in today’s data-driven world.

DATA 101

Data Knowledge and Discovery

Introduction to the essential elements of data science through the examination of data sets drawn from a variety of fields. Explores data collection and management, exploration and visualization of data, modeling, computing, and ethical issues associated with data science.

DATA 202

Data Management and Visualization

Introduction to foundational concepts and techniques in the management and presentation of data for effective data-informed decision making. Explores data storage and indexing strategies, data warehousing, metadata management, visualization of time-series and geospatial data, and best practices for presenting data to inform decision making.

DATA 102

Data Stewardship and Ethics

Overview of the data life cycle, including creation, collection, assurance, description, discovery, integration, use, reuse, and preservation. Explores data management principles and the development and implementation of data life cycle management plans. Examines the legal, ethical, and technological challenges in developing and implementing data management policies.

DATA 203

Analytical Methods of Data Science

Survey of modern algorithms and methods in data science, focusing on how, why, and when various methods work. Includes topics in statistics, machine learning, and optimization.

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Related Programs, Certificates & Minors

CECS offers innovative, customizable majors, minors, and certificates in areas of emerging technology and the skills required by the workforce of the future.