Program Overview

Overview of the Online Master of Computer Science – Big Data Systems

The Online Master of Computer Science with a concentration in big data systems at Arizona State University is designed for individuals interested in harnessing the power of computing and machine learning to make sense of big data. This program focuses on designing scalable systems for capturing, processing, and interpreting large and complex data sets, as well as gaining analytical expertise to generate insights from data and inform decision-making for organizations.

Program Details

• Duration: The program can be completed in 18-36 months.
• Total Classes: 10 classes are required to complete the program.
• Weeks per Class: Each class is 7.5 weeks long.
• Total Credit Hours: The program consists of 30 credit hours.
• Next Start Date: The next start date for the program is 01/12/2026.

Skills Developed

Upon completion of the program, students will develop a diverse skill set to acquire, store, and process large-scale data sets, as well as gain analytical expertise to mine information from the data. Specific skills include:

• Applying data mining technology to real-world applications.
• Creating tools that support entity, network analytics, text, and media analytics.
• Designing optimal solutions for a given set of application-driven constraints.
• Making informed decisions about data storage, indexing, querying, retrieval, and visualization.
• Reasoning about query optimization and execution alternatives.
• Using and developing real-time, online, and scalable processing systems.

Ideal Candidates

Ideal candidates for this program have a background in computer science and are working in computer programming or software engineering. The program is suited for those looking to advance their computer science career, particularly in the field of big data systems.

Professional Certification and Nondegree Enrollment Opportunities

As a nondegree graduate student, individuals can begin taking graduate-level computer science courses without being admitted to the master's program. This provides the opportunity to establish a high graduate GPA, try out courses to decide if they are interested in the full degree program, meet the English proficiency requirement, or earn a professional certification credential.

Featured Courses

The program includes a range of courses, such as:

• Data Mining: This course covers the concepts and techniques of data mining, including data preprocessing, pattern discovery, and data visualization.
• Data Processing at Scale: This course focuses on the principles and techniques of processing large-scale data sets, including parallel and distributed processing, and real-time processing.
• Data Visualization: This course explores the principles and techniques of data visualization, including data representation, visualization tools, and best practices.
• Engineering Blockchain Applications: This course covers the concepts and techniques of blockchain technology, including blockchain architecture, smart contracts, and blockchain-based applications.
• Statistical Machine Learning: This course introduces the concepts and techniques of statistical machine learning, including supervised and unsupervised learning, regression, and classification.

Career Opportunities

Graduates of the program can pursue a range of career opportunities, including:

• Cloud Support Associate
• Data Architect
• Data Engineer
• Data Scientist
• Database Administrator
• Software Development Engineer

Faculty

The program is taught by award-winning faculty members in the field of computer science, including members of the National Academy of Engineering, National Academy of Sciences, and National Academy of Inventors.

Accreditation

The program is accredited by the Higher Learning Commission and is ranked among the top 25% of all accredited engineering programs in the nation.

Tuition

The total cost of the degree program is $15,000, or $1,500 per 3-credit course. There are no textbooks required for the courses, and no additional fees.

Admission Requirements

Admission requirements for the program include:

• A minimum cumulative GPA of 3.00 in the last 60 credit hours of a four-year undergraduate degree.
• Completion of an undergraduate degree in computer science from an accredited university.
• Proficiency in programming languages such as C, C++, Java, Python, and HTML.
• Experience with data structures and algorithms, including sorting algorithms, hash tables, binary search trees, heaps, and red-black trees.

English Proficiency

If all college degrees are from a country outside of the U.S., applicants may need to demonstrate English proficiency through TOEFL, IELTS, PTE, or Duolingo scores.

Application Deadlines

Applicants with international credentials have an application deadline of six weeks prior to the selected session start date. All other applicants have an application deadline of four weeks prior to the selected session start date.

How to Apply

To apply, submit an online application and pay the application fee, send official transcripts to ASU's graduate admission services, and provide proof of English proficiency if necessary.

The above response provides a detailed overview of the Online Master of Computer Science – Big Data Systems program at Arizona State University, including program details, skills developed, ideal candidates, professional certification and nondegree enrollment opportunities, featured courses, career opportunities, faculty, accreditation, tuition, admission requirements, English proficiency, application deadlines, and how to apply.