Computer Science (Big Data Systems), MCS
Big Data, Consistency of data, Cybersecurity, Data analysis and mining, Data clouds, Data models and semantics, Data reduction and summarization, Data visualization, Heterogeneous data management and processing, Multi-dimensional data, Optimization of data processing, Real-time data management and processing, Scalable data managment and processing, Spatio-temporal, multimedia, and social data, approved for STEM-OPT extension, structured, semi-structured, and unstructured data
Help meet the growing need for data scientists and engineers who can architect, implement and manage large data systems. Learn the skills that will give you a competitive advantage in securing employment.
This concentration within the MCS degree program is designed for graduate students who want to pursue a thorough education in the area of big data systems.
Students acquire the knowledge, skills and expertise needed to design scalable systems (parallel, distributed and real time) that acquire, store, process and access large-scale heterogeneous multisource data, and they learn to use analytical tools to mine information from the data.
Graduates are able to choose and deploy the appropriate data management processing and analysis systems with a suitable structured or unstructured data model that a particular task and domain application needs.
This program may be eligible for an Optional Practical Training extension for up to 36 months. This OPT work authorization term may help international students gain skills and experience in the U.S. Those interested in an OPT extension should review ASU degrees that qualify for the STEM-OPT extension at ASU's International Students and Scholars Center website.
The OPT extension only applies to students on an F-1 visa and does not apply to students completing the degree through ASU Online.
- College/school:
Ira A. Fulton Schools of Engineering
- Location: Online
Acceptance to the graduate program requires a separate application. Students typically receive approval to pursue the accelerated master’s during the junior year of their bachelor's degree program. Interested students can learn about eligibility requirements and how to apply.
30 credit hours and a portfolio
Required Core Areas (9 credit hours) Concentration (9 credit hours) Restricted Electives (6 credit hours) Electives (6 credit hours) Culminating Experience (0 credit hours) Additional Curriculum Information Coursework selected as part of the area core may not be used as elective coursework on the same plan of study. Students should check with their academic advisor to ensure that the total number of credit hours of their plan of study is equal to 30. The concentration coursework cannot be used as part of the area core on the same plan of study. Students must complete concentration course requirements as listed and complete different coursework for each of the core areas in applications, foundations and systems. At least 24 of these hours must be CSE 5XX credits at ASU. A maximum of four CSE 598 courses may be allowed as elective coursework. Up to six credit hours of 400-level courses may be applied to the plan of study. All 30 credit hours must be from formal coursework. CSE 590 is not allowed as part of the MCS program plan of study. All Master of Computer Science program students must complete a project portfolio based on two courses in which the student received a grade of "B" (scale is 4.00 = "A") or higher.
applications (3)
foundations (3)
systems (3)
CSE 511 Data Processing at Scale (3)
CSE 575 Statistical Machine Learning (3)
CSE 578 Data Visualization (3)
portfolio (0)
Students should see the academic unit for the list of courses approved for electives and each core area in applications, foundations and systems.
Applicants must fulfill the requirements of both the Graduate College and the Ira A. Fulton Schools of Engineering.
Applicants are eligible to apply to the program if they have earned a bachelor's or master's degree in computer science, computer engineering or a closely related area from a regionally accredited institution.
Applicants must have a minimum cumulative GPA of 3.00 (scale is 4.00 = "A") in the last 60 hours of their first bachelor's degree program, or they must have a minimum cumulative GPA of 3.00 (scale is 4.00 = "A") in an applicable master's degree program.
Applicants must submit:
- graduate admission application and application fee
- official transcripts
- statement of purpose or curriculum vitae
- proof of English proficiency
Additional Application Information
An applicant whose native language is not English must provide proof of English proficiency regardless of their current residency.
Students assigned any deficiency coursework upon admission must complete those classes with a grade of "C" (scale is 4.00= "A") or higher within two semesters of admission to the program. Deficiency courses include:
CSE 230 Computer Organization and Assembly Language Programming
CSE 310 Data Structures and Algorithms
CSE 330 Operating Systems
CSE 340 Principles of Programming Languages or CSE 355 Introduction to Theoretical Computer Science
The applicant's undergraduate GPA and depth of preparation in computer science and engineering are the primary factors affecting admission.
ASU offers this program in an online format with multiple enrollment sessions throughout the year. Applicants may view the program’s ASU Online page for program descriptions and to request more information.
| Session | Modality | Deadline | Type |
|---|---|---|---|
| Session A/C | Online | 07/21 | Final |
| Session B | Online | 09/17 | Final |
| Session | Modality | Deadline | Type |
|---|---|---|---|
| Session A/C | Online | 12/13 | Final |
| Session B | Online | 01/31 | Final |
| Session | Modality | Deadline | Type |
|---|---|---|---|
| Session A/C | Online | 04/18 | Final |
Graduates who complete the Master of Computer Science program are able to analyze key theories, algorithms and software modules used in the field of computer science.
Career examples include:
- computer network architect
- computer system analyst
- computer systems engineer
- data scientist or engineer
- machine learning, AI computer vision engineer
- software developer
- software engineer
Computer Science and Engineering Program
|
CTRPT 105
On Campus: SCAI.Grad.Admission@asu.edu
ASU Online: mcsonline@asu.edu
480-965-3199
3 year programs
These programs allow students to fast-track their studies after admission and earn a bachelor's degree in three years or fewer while participating in the same high-quality educational experience of a 4-year option. Students should talk to their academic advisor to get started.
Accelerated master's
These programs allow students to accelerate their studies to earn a bachelor's plus a master's degree in as few as five years (for some programs).
Each program has requirements students must meet to be eligible for consideration. Acceptance to the graduate program requires a separate application. Students typically receive approval to pursue the accelerated master’s during the junior year of their bachelor's degree program. Interested students can learn about eligibility requirements and how to apply.
