Study Programme Details
City: | |
Country: | United States |
Admission Sessions: | Autumn Session, Summer Session, Spring Session |
Study Format: | Part Time |
Mode of Study: | Online |
About this Study Course
Immerse yourself in the forefront of data analytics with Franklin University’s M.S. in Data Analytics. This program empowers you with a comprehensive skill set, combining statistical prowess, programming acumen, and effective communication to unravel the potential of big data. Stay ahead of industry trends as you delve into cutting-edge tools and platforms, positioning yourself as a strategic player in the data-driven landscape.
Overview
In today’s competitive landscape, organizations seek professionals with a blend of programming, analytics, and communication skills. The M.S. in Data Analytics at Franklin University not only meets this demand but prepares you for the analytics jobs of today and tomorrow. With a projected 9% growth in demand for data analytics professionals, this program equips you with a robust curriculum covering statistics, programming, data management, data visualization, and advanced analytics. Dive into big data technologies such as Hadoop, MapReduce, Data Warehouse, SQL, No SQL, and In-memory Databases, gaining a competitive edge in the job market. Franklin’s 100% online format ensures convenience and flexibility, supported by expert instructors, real-world experience, and dedicated faculty.
Admission Requirements
- Bachelor’s degree from a CHEA-recognized institution with a minimum GPA of 2.75.
- Conditional enrollment for a 2.5 GPA, subject to achieving a minimum of “B” in the first graduate-level course.
- English Language Proficiency demonstrated through citizenship, degree from an English-speaking institution, or proficiency exam scores.
- Issues in Database Management
- Data Visualization & Reporting
- Big Data Analytics and Data Mining
- Applied Machine Learning
- Computing for Data Analytics
32 Credit Hours
the fee of course is 670USD per credit hours
Future Career Outcomes
Graduates of the M.S. in Data Analytics are primed for success in a data-centric landscape. With proficiency in Python, R, and industry-standard tools, they step into roles such as Data Scientist, Big Data Engineer, and Business Intelligence Analyst. Future career outcomes include leadership positions, consulting roles, and the opportunity to shape organizational strategies through data-driven insights.