Bachelor's in Computer Science: Big Data Analytics Degree Emphasis
Earn a Computer Science Bachelor’s Degree in Big Data Analytics
In the Bachelor of Science in Computer Science (CS) with an Emphasis in Big Data Analytics program at Grand Canyon University (GCU), you will gain exposure to foundations in data science and computer software design, developing your capability to analyze big data. You will learn to assess existing algorithms and methodologies, and build your own as a way to engage in continuous development.
The College of Science, Engineering and Technology at GCU has established many rigorous goals for students in the BS in computer science big data analytics degree program. These expected outcomes include:
- An ability to apply knowledge of computing, mathematics and statistics
- An ability to analyze a problem, and identify and define the scientific methodologies appropriate to its solution
- An ability to design, implement and evaluate a computer-based system, process or program
- An ability to work in a team
- An understanding of all responsibilities related to CS and big data analytics work
You will acquire a framework of knowledge in computer science and other sciences, with a deep dive into Calculus, Linear Algebra, Discrete Math and Statistics, at the College of Science, Engineering and Technology. You will progress through sequentially arranged coursework that is in-depth in nature and broad in scope. This multidisciplinary degree covers relevant topics in chemistry, biology and human-computer interaction.
The Bachelor of Science in Computer Science with an Emphasis in Big Data Analytics program is accredited by the Computer Science Accreditation Commission of ABET.
For more information on the ABET accreditation of computer science programs and other university licensures, please visit our University Accreditation and Regulations page.
Immerse Yourself in the Rising Field of Big Data Analytics
With a big data degree, you will learn how to work in a variety of information systems. You will learn to create systems that collect and analyze data with greater speed and efficiency. Once in your career, big data and analytics degree graduates help to improve and support an organization's processes and extraction of actionable information from data collected.
To do all of this important data analysis work, your coursework in the computer science (big data) degree emphasis will have theoretical and hands-on courses, where you learn about:
- Large-scale data processing
- Statistical analysis
- Computer programming using discipline-specific tools and methods
- Data mining and interpretation
- Pattern analysis
- System architecture and organization
- Information assurance and security
- Data modeling
- Social network theory
- Search engine design
In addition, this big data analytics degree requires you to complete a senior capstone project, spanning the entire senior year. You will work in teams to pursue real-world research and design projects, including virtual and augmented reality, data science and machine learning. The capstone experience enables students to demonstrate their accomplishments as members of the GCU learning community.
Career Paths for Graduates With a Computer Science in Big Data Analytics Degree Emphasis
After graduating with a BS in computer science (big data) degree emphasis, you will have the capacity to adopt new developments in technologies in computer science. You will be able to apply the theoretical foundations of computer science to solve real-world problems in fast-paced, high tech environments. You will also have the communication and collaboration skills to work with all interested stakeholders.
These technical and personal skills may enable our big data and analytics degree graduates into work as:
- Computer and information system managers
- Computer programmers
- Software developers
- Information security analysts
- Software quality assurance analysts and testers
- Data scientists
If you are ready to start learning more about your future in software development and big data analytics, join us at GCU today. The Bachelor of Science in Computer Science with an Emphasis in Big Data Analytics degree may be just the right program for you.
BS in Computer Science - Big Data Analytics Degree Emphasis FAQs
Big data is a career field that covers various industries and multiple departments, such as marketing and sales, development and strategic management. The many companies that manage large amounts of data require big data experts to help all the numbers make sense. With this in mind, there will always be a need for well-educated, big data professionals in various organizations.
While these two work together, they are not exactly the same. Big data refers to using software systems to manage large amounts of data, discover patterns and use that data to enhance a company’s competitive edge in the market. Data science, on the other hand looks more closely at these specific revelations that come about from big data analysis, and creates algorithms and statistical models from the big data.
While coding skills may be good to have in a big data analytic career, coding is not a main component of big data analytics. Basic coding skills may be useful at times, however advanced coding is not typically required for big data analysts. Big data focuses on using software systems, data management programs and analytic techniques to discover trends and correlations in various data sets and systems.
There are multiple degree offerings within a computer science discipline that may cover areas of data analytics and provide you with a solid background and understanding. However, a bachelor’s such as a big data degree is focused on teaching you the specific math, analytics and methodologies you’ll need to pursue a career in data analytics. With your bachelor’s, you can then go on to explore further education options and advance your position in the field of data analytics. You may choose to pursue a Master of Science in Data Science degree, where you will perform deeper research and apply your learnings to modern day data systems.
General Education Requirements
General Education coursework prepares Grand Canyon University graduates to think critically, communicate clearly, live responsibly in a diverse world, and thoughtfully integrate their faith and ethical convictions into all dimensions of life. These competencies, essential to an effective and satisfying life, are outlined in the General Education Learner Outcomes. General Education courses embody the breadth of human understanding and creativity contained in the liberal arts and sciences tradition. Students take an array of foundational knowledge courses that promote expanded knowledge, insight, and the outcomes identified in the University's General Education Competencies. The knowledge and skills students acquire through these courses serve as a foundation for successful careers and lifelong journeys of growing understanding and wisdom.
Upon completion of the Grand Canyon University's University Foundation experience, students will be able to demonstrate competency in the areas of academic skills and self-leadership. They will be able to articulate the range of resources available to assist them, explore career options related to their area of study, and have knowledge of Grand Canyon's community. Students will be able to demonstrate foundational academic success skills, explore GCU resources (CLA, Library, Career Center, ADA office, etc), articulate strategies of self-leadership and management and recognize opportunities to engage in the GCU community.
- UNV-112, Success in Science, Engineering and Technology & Lab: 4
- UNV-103, University Success: 4
- UNV-303, University Success: 4
- UNV-108, University Success in the College of Education: 4
Graduates of Grand Canyon University will be able to construct rhetorically effective communications appropriate to diverse audiences, purposes, and occasions (English composition, communication, critical reading, foreign language, sign language, etc.). Students are required to take 3 credits of English grammar or composition.
- UNV-104, 21st Century Skills: Communication and Information Literacy: 4
- ENG-105, English Composition I: 4
- ENG-106, English Composition II: 4
Graduates of Grand Canyon University will be able to express aspects of Christian heritage and worldview. Students are required to take CWV-101/CWV-301.
- CWV-101, Christian Worldview: 4
- CWV-301, Christian Worldview: 4
Graduates of Grand Canyon University will be able to use various analytic and problem-solving skills to examine, evaluate, and/or challenge ideas and arguments (mathematics, biology, chemistry, physics, geology, astronomy, physical geography, ecology, economics, theology, logic, philosophy, technology, statistics, accounting, etc.). Students are required to take 3 credits of intermediate algebra or higher.
- MAT-154, Applications of College Algebra: 4
- MAT-144, College Mathematics: 4
- PHI-105, 21st Century Skills: Critical Thinking and Problem Solving: 4
- BIO-220, Environmental Science: 4
Graduates of Grand Canyon University will be able to demonstrate awareness and appreciation of and empathy for differences in arts and culture, values, experiences, historical perspectives, and other aspects of life (psychology, sociology, government, Christian studies, Bible, geography, anthropology, economics, political science, child and family studies, law, ethics, cross-cultural studies, history, art, music, dance, theater, applied arts, literature, health, etc.). If the predefined course is a part of the major, students need to take an additional course.
- HIS-144, U.S. History Themes: 4
- PSY-102, General Psychology: 4
- SOC-100, Everyday Sociology: 4
Required General Education Courses
This course presents the fundamentals of algebra and trigonometry with some applications; it provides the background and introduction for the study of calculus. Topics include review of linear equations and inequalities in one and multiple variables; functions and their graphs; polynomial, rational, exponential, logarithmic, and trigonometric functions; systems of equations and matrices; and sequences and series. Slope and rate of change are introduced to set up the concepts of limits and derivatives. There is an emphasis on both an understanding of the mathematical concepts involved as well as their applications to the principles and real-world problems encountered in science and engineering. Technology is utilized to facilitate problem analysis and graphing. Prerequisite: MAT-134 or MAT-154.
This course provides a rigorous treatment of the concepts and methods of elementary calculus and its application to real-world problems. Topics include differentiation, optimization, and integration. Software is utilized to facilitate problem analysis and graphing. Prerequisite: MAT-261 or ESG-162/162L.
This course is a study of biological concepts emphasizing the interplay of structure and function, particularly at the molecular and cellular levels of organization. Cell components and their duties are investigated, as well as the locations of cellular functions within the cell. The importance of the membrane is studied, particularly its roles in controlling movement of ions and molecules and in energy production. The effect of genetic information on the cell is followed through the pathway from DNA to RNA to protein. Co-requisite: BIO-181L.
This lab course is designed to reinforce principles learned in BIO-181 through experiments and activities which complement and enhance understanding of macromolecules, cell membrane properties, cellular components, and their contribution to cell structure and function. Assignments are designed to relate cellular processes such as metabolism, cell division, and the flow of genetic information to cell structure. Co-requisite: BIO-181.
This course reviews the basic principles, tools, and techniques used in computer applications that enable communication, visualization, access to information, learning and entertainment. Students learn the methods of designing, implementing and evaluating techniques for effective communication in a technical, business, education or entertainment context. The laboratory reinforces and expands learning of principles introduced in the lecture. Hands-on activities focus on experiencing and implementing concepts discussed in the lecture. Students create applications that communicate ideas efficiently and are easy to use. This is a writing intensive course. Prerequisites: CST-201, MAT-262, and (CST-217 or CST-341).
This course provides an insight into professional communications and conduct associated with careers in science, engineering and technology. Students learn about the changing modes of communication in these disciplines recognizing the advances in digital communications. They gain practical experience developing and supporting a thesis or position through written, oral, and visual presentations prepared and delivered individually and in groups. Students will explore concepts and issues in professional ethics and conduct such as privacy, discrimination, workplace etiquette, cyber-ethics, network and data security, identity theft, ownership rights and intellectual property. This is a writing intensive course.
This course introduces the fundamental concepts and syntax of the Java programming language. The course focuses on object-oriented techniques in Java with an emphasis on problem solving and fundamental algorithms.
This course provides an in-depth coverage of object-oriented programming using most current application programming methods, languages, and tools. Students will design, create, run, and debug applications. The course emphasizes the development of correct, well-documented programs using object-oriented programming concepts. Prerequisite: CST-111 or CST-105.
This course is a calculus-based study of basic concepts of physics, including motion; forces; energy; the properties of solids, liquids, and gases; and heat and thermodynamics. The mathematics used includes algebra, trigonometry, and vector analysis. A primary course goal is to build a functional knowledge that allows students to more fully understand the physical world and to apply that understanding to other areas of the natural and mathematical sciences. Conceptual, visual, graphical, and mathematical models of physical phenomena are stressed. Students build critical thinking skills by engaging in individual and group problem-solving sessions. Prerequisite: MAT-262. Co-Requisite: PHY-121L.
This calculus-based course utilizes lab experimentation to practice concepts of physical principles introduced in the PHY-121 lecture course. Students are able to perform the proper analysis and calculations to arrive at the correct quantifiable result when confronted with equations involving gravity, sound, energy, and motion. Prerequisite: MAT-262. Co-Requisite: PHY-121.
This course provides a rigorous treatment of the concepts and methods of integral, multivariable, and vector calculus and its application to real-world problems. Prerequisite: MAT-262.
This in an introductory course in discrete mathematics with digital logic. Topics covered include Boolean algebra, circuits, number theory, sequences, recursion, sets, functions, and counting. An emphasis will be placed on writing computer programs that address key concepts discussed in lecture. Prerequisite: MAT-261 or CST-111 or CST-105.
This course covers classical algorithms and data structures, with an emphasis on implementation and application in solving real-world computational problems. The course focuses on algorithms for sorting, searching, string processing, and graphs. Students learn basic strategies to evaluate divide-and-conquer, recursive backtracking, and algorithm efficiency. Hands-on activities focus on writing code that implements concepts and algorithm implementation techniques. Prerequisite: CST-210 or CST-239 or CST-135 or CST-250 or CST-227.
This course provides students with the technical skills required to design and implement a database solution using a SQL server. Students use data definition language (DDL) to create and delete database objects, and data manipulation language (DML) to access and manipulate those objects. Students gain hands-on experience with database design, data normalization, SQL sub-queries, creating and using views, understanding and working with data dictionaries, and loading and unloading databases. The laboratory reinforces and expands learning of principles introduced in the lecture. Hands-on activities focus on writing code that implements concepts discussed in the lecture course, specifically creating databases and SQL queries. Prerequisite: CST-105.
This course is intended primarily for mathematics, science, and engineering students. The goal of the course is to impart the concepts and techniques of modern linear algebra (over the real scalar field) with a significant level of rigor. Students write clearly about the concepts of linear algebra (definitions, counterexamples, simple proofs), and apply theory to examples. The course emphasizes the practical nature of solutions to linear algebra problems. Students implement some of these solutions, where appropriate, as computer programs. Prerequisite: MAT-264 or MAT-253
This course introduces current trends in computer architecture with a focus on performance measurement, instruction sets, computer arithmetic, design and control of a data path, pipelining, memory hierarchies, input and output, and a brief introduction to multiprocessors. The laboratory reinforces and expands learning of principles introduced in the lecture course. Hands-on activities focus on writing assembly language code that implements concepts discussed in the lecture course, focusing on registers, processes, threads, and I/O management. Prerequisites: (CST-210 and CST-215), or EEE-315.
This course covers the role of statistics in engineering, probability, discrete random variables and probability distributions, continuous random variables and probability distributions, joint probability distributions, random sampling and data description, point estimation of parameters, statistical intervals for a single sample, and tests of hypotheses for a single sample. Prerequisite: MAT-253 or MAT-264.
This writing-intensive course teaches students to develop innovative solutions to real-world problems, developing and testing hypotheses as they learn to create a new product or service.
This course covers applications of differential equations in modeling and simulation. Students use mathematical models for continuous and discrete simulation, and develop applications for complex systems across a variety of domains. Students learn how to represent a system by a model and then execute the model to generate and statistically analyze data. The laboratory reinforces and expands learning of principles introduced in the lecture. Hands-on activities focus on writing code that implements differential equation based modeling algorithms and visual simulations. Prerequisite: CST-201, CST-215, MAT-264.
This course explains the concepts, structure, and mechanisms of modern operating systems. The course covers computational resources, such as memory, processors, networks, security, and how the programming languages, architectures, and operating systems interact. The laboratory reinforces and expands learning of principles introduced in the lecture. Hands-on activities focus on writing a shell that implements process management, file management, and I/O management. Prerequisite: CST-307.
This course introduces the syntax and semantics of programming languages, program construction and software design. Lab activities will focus on analyzing the characteristics of context-free languages and solving a variety of languages construction challenges. Prerequisite: CST-201, CST-307.
This course introduces modern theories of machine learning and design & implementation models for large scale quantitative, image, and text information systems. The machine learning and information retrieval methodologies include Boolean, vector space, probabilistic, inference net, and language modeling. Students will acquire hands-on experience by implementing models such as clustering algorithms, automatic text categorization, and experimental evaluation. As an introduction to data science theory and techniques, students will experiment with supervised and unsupervised learning algorithms, intelligent text summarization, topic detection, tagging, and tracking. The laboratory reinforces and expands learning of principles introduced in the lecture. Hands-on activities focus on implementing techniques for efficiently managing and manipulating very large data sets and build machine learning models. Prerequisites: MAT-374 and (CST-217 or SYM-400) and MAT-345.
The first capstone course provides students the opportunity to work in teams to tackle real world applied research and design projects in their chosen area of interest. Students develop a project proposal, conduct a feasibility study, learn to protect intellectual property, develop teamwork skills, budgets, and a schedule for completing the project. Students conduct extensive research, integrate information from multiple sources, and work with a mentor through multiple cycles of feedback and revisions. Students use this course to further develop technical writing and business presentation skills. This is a writing intensive course. Prerequisites: CST-307, CST-315 and department approval.
This course builds upon knowledge already acquired in the areas of system architecture and operating systems and focuses on the core issues of information security. Students learn fundamental aspects, security mechanisms, operational issues, security policies, and attack types. Prerequisite: ITT-121 or CST-210 or CST-221.
This course covers 2D and 3D concepts, algorithms, and implementation methods using shader-based programming. Main topics covered include coordinate systems, transformations, material simulation, and animation. The laboratory reinforces and expands learning of principles introduced in the lecture. Hands-on activities focus on writing vertex shaders and fragment shaders to implement light equations for coloring effects, textures, materials, and animation. Prerequisites: CST-201, MAT-262, and MAT-345.
This course reviews the concepts and tools used in the development of compilers. Students synthesize topics covered in previous courses: formal languages, data structures, and computer architecture. The course reinforces the principles of software engineering and development through a complete cycle of building a working compiler. The laboratory reinforces and expands learning of principles introduced in the lecture. Hands-on activities focus on writing a compiler including a lexer, parser, semantic analyzer, code generator, and optimizer. Prerequisites: CST-301 and MAT-374.
This course provides a comprehensive introduction to neural networks and deep learning. The location, retrieval, and conversion of raw data into usable information is accomplished by implementing a variety of neural network models. Students implement deep learning algorithms for organizing and searching very large data collections, like those typically found in enterprise databases and on websites. Students use clustering and categorization to generate various information taxonomies based on document ranking, evaluation, and classification. The laboratory reinforces and expands deep learning principles introduced in the lecture. Hands-on activities focus on using neural networks for performing data mining on a large business database and extracting trends and actionable information. Prerequisites: MAT-374 and (CST-217 or SYM-400)and MAT-345.
The second capstone course provides students the opportunity to implement and present the applied research project designed, planned, and started in the first capstone course. The capstone project is a culmination of the learning experiences while a student in the Computer Science program. Students conduct extensive research, integrate information from multiple sources, and work with a mentor through multiple cycles of feedback and revision. This is a writing intensive course. Prerequisite: Successful completion of STG-451 with a grade of C or better.
This course is a direct continuation of ITT-305. It expands the coverage of information security topics to include security domains, forensics, information states, security services, threat analysis, and vulnerabilities. Prerequisite: ITT-305.
This course focuses on very large web-based sources of information such as social networks and semantic networks. Students analyze dynamic data and trends, connections (links), and patterns of self-organization. Students then utilize intelligent inferential techniques to interpret patterns in the collected information and translate them into actionable items. Hands-on experiences include marketing, organizational structure, security, and human analytics. Prerequisites: MAT-374 and (CST-217 or SYM-400) and MAT-345.
This course surveys current advances in computer science. Topics vary by semester and include current and emerging practice in computer science. Lab activities will focus on hands-on projects with a variety of technologies, devices, and programming languages. Prerequisite: CST-315, CST-301.
Join Grand Canyon University’s vibrant and growing campus community, with daytime classes designed for traditional students. Immerse yourself in a full undergraduate experience, complete with curriculum designed within the context of our Christian worldview.
* Please note that this list may contain programs and courses not presently offered, as availability may vary depending on class size, enrollment and other contributing factors. If you are interested in a program or course listed herein please first contact your University Counselor for the most current information regarding availability.
* Please refer to the Academic Catalog for more information. Programs or courses subject to change.