Graduate Certificate in Big Data

The purpose of this certificate is to provide students with a solid foundation in modern tools and technologies to succeed as a machine learning applications and deployment engineer. The emphasis is on foundational methods spanning data storage and querying, data analysis, and data visualization. Specific emphasis is also placed on social media data, one of the fastest growing segments of the big data economy. The certificate prepares students in state-of-the-art languages and pipelines for machine-learning algorithm implementation over massive datasets.

Learning Outcomes: Students who complete this certificate will be able to

• Explain how Big Data applications are built using architectures, such as Apache Hadoop, Apache Spark, NoSQL, and MongoDB.

• Use object-oriented programming to implement data processing pipelines using Python and Big Data architectures.

• Tackle practical programming issues underlying storing, retrieving, accessing, and processing large datasets.

• Implement machine learning methods and apply them to large scale datasets.

• Implement specialized pipelines for analyzing social media data, including network analysis, information extraction, and sentiment analysis.

• Apply fundamentals of data and information visualization to deliver visual insights.

• Analyze real-world datasets to develop applications.

Target Audience:

The target audience is professionals in organizations or fields that use large data sets and would pursue the certification for job knowledge and career enhancement. Those students will be admitted as non-degree seeking, MIT-Commonwealth students.

We also expect graduate students, full- or part-time and currently enrolled in a VT graduate degree program that involves the use of big data, to be interested in adding this certification as a supplement to their degree.

How To Apply:

External applications should complete the VT-MIT online application as a certificate-seeking student at https://vtmit.vt.edu/admissions/apply-now.html

MIT Graduate Certificates

Admission Requirements for the Graduate Certificate in Big Data

Virginia Tech requires admission to the Graduate School and completion of a Graduate Certificate Application for both degree- and non-degree seeking certificate applicants. 

Degree-seeking applicants: The Graduate School requires completion of a bachelor’s degree from an accredited institution with a GPA of 3.0 or greater for admission to Certificate Status. MIT applicants with an undergraduate GPA less than 3.0 may qualify for Commonwealth Campus admission and will need to comply with MIT requirements of Commonwealth Campus status prior to admission to Certificate Status. Students pursuing a degree and a certificate simultaneously are classified within their degree program.

For students interested in pursuing both the MIT degree and the certificate(s), no more than fifty percent of certificate courses will be included toward completion of the MIT degree. 

Non-degree seeking applicants: Applicants that wish to obtain a graduate certificate only, without being enrolled in a VT degree program, may apply by completing an abbreviated application to MIT's Certificate program. The Graduate Certificate Application Form is required after admission.

Applicants must meet the following criteria:

• Earn a GPA of 3.0 or greater or credits earned during the last half of their undergraduate degree.

• Submit official transcripts.

• Meet the academic background requirements of the admitting academic unit.

• International Applicants must submit scores from the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS). 

• Earn a minimum TOEFL score of 577 paper-based (PBT) or 90 internet-based test (iBT). For the iBT, earn a minimum of 20 on each subject test (Listening, Speaking, Reading, and Writing).

• Earn a minimum IELTS score of 6.5.

• Some departments have higher TOEFL or IELTS score requirements than those set by the Graduate School.

Course Requirements for the Graduate Certificate in Big Data

Number of Credit Hours:

A total of nine credit hours are required. Transfer credits are not permitted. Students must maintain a minimum GPA of 3.0 in the designated courses.

Required Courses: 

CS 5044 Object-Oriented Programming with Java: Object-oriented programming concepts and the Java programming language. The application of design strategies, notations, and patterns related to object-oriented systems. Techniques and libraries for developing applications related to the World Wide Web. Pre: Proficiency in a high-level programming language (e.g. C#, C, C++, or Java), practical training, and/or work experience related to developing computer software and systems.

CS 5644 Machine Learning with Big Data: Basic principles and techniques for big data analytics, including methods for storing, searching, retrieving, and processing large datasets; introduction to basic machine learning libraries for analyzing large datasets; data visualization; case studies, with real-world datasets. Pre: CS 5044. 

CS 5664 Social Media Analytics: Social media platforms, media feeds, and data formats; machine learning and graph theory foundations of social media analytics; forms of social media analytics – text analytics, network analytics, and action analytics; forecasting models and applications, including in marketing, event tracking, surveying, and A/B testing. Pre: CS 5044.