Master of Science in Data Science (MSDS)

HCU’s Unique Ethical Stewardship Training

What sets HCU’s MSDS program apart is its unique fusion of technical expertise and ethical considerations, all viewed through a Christian perspective. In a landscape where data ethics and privacy concerns are increasingly critical, our graduates emerge not only as skilled data scientists but as responsible stewards of information.

You’ll be prepared to tackle complex challenges, drive innovation, and make data-driven decisions that can positively impact businesses, communities, and society at large. Whether you’re a recent graduate looking to specialize in this high-demand field, or a working professional seeking to pivot your career, HCU’s Master of Science in Data Science provides the knowledge, skills, and ethical foundation to thrive in the data-centric future.

Comprehensive Data Science Curriculum

The MS in Data Science degree plan consists of 33 semester hours of core curriculum. Graduates of this program must complete all 33 credit hours with a grade of B or better and maintain an overall GPA of 3.0 or higher. Additionally, graduates are required to complete at least one graduate capstone project. Beginning in the 2025/2026 Academic Year, F-1 visa students participating in the CPT program must complete DSCI 5395 – Applied Learning Practicum.

The Master of Science in Data Science at Houston Christian University offers a comprehensive curriculum designed to equip students with the skills and knowledge needed to excel in the rapidly evolving field of data science. Our courses blend theoretical foundations with practical applications, ensuring graduates are ready to tackle real-world challenges.

Review degree plan
Low-residency degree plan

Data Science Courses

• Introduction to Data Science: Dive into the fundamentals of data science, exploring key concepts, methodologies, and tools that form the backbone of the field.
• Statistics for Data Science: Master advanced statistical methods crucial for data analysis, hypothesis testing, and predictive modeling.
• Machine Learning: Delve into the world of algorithms that enable computers to learn from data, covering both supervised and unsupervised learning techniques.
• Data Mining and Visualization: Uncover hidden patterns in complex datasets and learn to communicate insights through compelling visual representations.
• Big Data Analytics: Tackle the challenges of processing and analyzing massive datasets using cutting-edge tools and frameworks.
• Python Programming and R Programming: Gain proficiency in two of the most powerful programming languages for data manipulation, analysis, and visualization.
• Data Ethics and Privacy: Navigate the ethical considerations and legal implications of data science, ensuring responsible and trustworthy practices.
• Natural Language Processing: Explore techniques for analyzing and generating human language, opening doors to applications in sentiment analysis, chatbots, and more.
• Deep Learning: Dive into advanced neural network architectures, paving the way for breakthroughs in image recognition, speech processing, and other complex tasks.

The curriculum combines lectures, hands-on projects, and real-world case studies, providing a rich, immersive learning experience. This degree program culminates in a capstone project, allowing students to apply their skills to solve a complex, real-world data science challenge.

With this robust curriculum, HCU data science degree graduates emerge not just with theoretical knowledge, but with the practical skills and experience needed to lead in the data-driven world of tomorrow.

Admissions Requirements

• Completed online application.
• Bachelor’s degree from an accredited institution, preferably in Computer Science or Computer Engineering; or an accredited Bachelor’s degree with a certification in a similar field of study such as Google, IBM, or Microsoft certificate.
• Bachelor’s degree must contain:
  • College-level Math course with a grade of C or higher.
  • College-level Statistics course with a grade of C or higher.
• 3.0 GPA or 2.5 GPA for conditional acceptance (where students must achieve a 3.0 GPS in the first nine credit hours for the program).
• For International Students:
  • Successful completion of the English Proficiency Test.
  • FTE (Foreign Transcript Evaluation of Bachelor’s degree transcript).

Ideal Data Science Degree Candidates

The MSDS program caters to:

• Recent graduates with backgrounds in computer science, statistics, mathematics, or related fields
• Working professionals seeking to transition into data science or enhance their current roles
• Analytical thinkers passionate about leveraging data to solve complex problems
• Individuals with a strong interest in technology and its applications across various industries

Successful students in this program typically possess:

• Strong quantitative and analytical skills
• Curiosity and a drive for continuous learning
• Excellent problem-solving abilities
• The capacity to work both independently and collaboratively
• A desire to apply data science ethically and responsibly
• Effective communication skills to translate technical findings into actionable insights

While prior coding experience is beneficial, it is not mandatory. The program’s core courses provide the necessary programming skills in key data science languages like Python and R.

Capstone Project and Applied Learning Practicum

Students apply their acquired skills to solve real-world data challenges, working on substantive projects that showcase their abilities to potential employers. This hands-on experience is crucial for bridging the gap between academic knowledge and practical application in the field.

Beginning in the 2025/2026 academic year, the Applied Learning Practicum offers students the opportunity to put their theoretical knowledge into practice through real-world experiences like internships or work placements. These experiences can take various forms: (1) alternative work/study, internships, cooperative education, (2) employment relevant to the student’s field of study, or (3) collaborative projects with faculty applying coursework to professional contexts.

Learning Modalities

This program is offered as a fully online program or as a low-residency program. The online program has several components that will be synchronous, meaning students will actively log in and stream lectures at specified times.

The low-residency option combines online learning with on-campus experiences. Each course includes one residency weekend session (Friday-Saturday) held at the HCU campus, where you will be required to attend two-day intensive sessions for hands-on learning and collaboration.

The data science field is experiencing unprecedented growth, with the U.S. Bureau of Labor Statistics projecting a remarkable 35% increase in employment from 2022 to 2032. Graduates of HCU’s MSDS program are well-positioned for exciting and lucrative careers across various industries.

Career Paths and Roles

• Data Scientist: The cornerstone role in the field, involving the analysis of complex datasets to extract actionable insights. Data scientists often work on predictive modeling, machine learning algorithms, and statistical analysis.
• Machine Learning Engineer: Focuses on designing and implementing machine learning models and AI systems. This role bridges the gap between data science and software engineering.
• Data Architect: Designs and manages an organization’s data infrastructure, ensuring efficient data storage, retrieval, and integration across systems.
• Big Data Engineer: Specializes in building and maintaining the infrastructure required to process and analyze large-scale datasets.
• AI Specialist: Develops artificial intelligence solutions, often working on cutting-edge projects involving natural language processing, computer vision, and robotics.
• Data Analytics Consultant: Provides expert advice to organizations on how to leverage data for strategic decision-making and process improvements.
• Business Intelligence Analyst: Focuses on using data to drive business strategy and improve operational efficiency.
• Quantitative Analyst: Applies mathematical and statistical methods to solve complex problems in finance and risk management.

Industry Applications

Data science skills are in high demand across numerous sectors, including:

• Technology: Driving innovation in areas such as recommendation systems, user experience optimization, and predictive maintenance
• Healthcare: Improving patient outcomes through predictive analytics, personalized medicine, and medical image analysis
• Finance: Enhancing risk assessment, fraud detection, and algorithmic trading strategies
• Energy: Optimizing resource allocation, predicting equipment failures, and improving energy efficiency
• E-commerce: Personalizing customer experiences, optimizing supply chains, and predicting market trends
• Manufacturing: Implementing predictive maintenance, quality control, and process optimization
• Transportation: Developing autonomous vehicles, optimizing logistics, and improving traffic management
• Government: Enhancing public services, improving policy decisions, and addressing societal challenges

International Student Internship Opportunities

This program includes off-campus internship opportunities for international students to gain real-world experience as part of the establish curriculum. Learn more about applying to HCU as an international student.

Career Transformation with Data Science

The Master of Science in Data Science at Houston Christian University is more than just a degree – it’s a gateway to becoming a leader in a field that’s shaping the future. By combining technical expertise with ethical considerations, HCU graduates are prepared to make significant impacts across industries while upholding Christian values.

In a world increasingly driven by data, the skills and knowledge gained through this program are invaluable. Graduates will be equipped to tackle complex challenges, drive innovation, and contribute to advancements that can positively impact society.

Ready to unlock the power of data and advance in this exciting field? Apply now.