Master of Science in Big Data Analytics
Program Overview
The Master of Science in Big Data Analytics (MSBDA) program is designed to provide students with the necessary tools and approaches for capturing, pipelining, processing, and analyzing both massive batch datasets and streams of data.
Whether it is structured transactional data, semi-structured, or even unstructured data gathered from Web communities, clickstreams, or data collected from sensors, or enterprise information systems, the students will learn how to apply Big Data management and analytics techniques to uncover hidden patterns, unknown correlations, trends, customer preferences, and other useful business information. The analytical findings can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, and competitive advantages over rival organizations.
Approach
In addition to covering the fundamental principles and concepts behind Big data processing, such as scalable distributed processing and storage, NoSQL data models, resilient data pipelining, data visualization, model building using Machine Learning, and Natural Language Processing. The MS in Big Data Analytics emphasizes learning by doing through the use of Apache open source and proprietary platforms and tools for course assignments and case studies, as well as for final projects.
Market Demand
Data is the new “oil”. Enterprises and research labs are massively transforming their IT into building data pipes in order to drive decisions and extract value to stay ahead of the competition. The market for qualified Big Data engineers is in dire need of qualified graduates, ready to hit the ground running.
Acquired skills
The Master of Science in Big Data Analytics is designed to graduate well-rounded engineers, equipped with skills along the whole data value chain ranging from acquisition to analytics. Specifically, graduates will be able to:
- Setup adequate data architectures, models, processing and pipelining environments for Big Data;
- Apply a variety of Big Data analytics techniques (including data mining and statistical techniques) for prediction and recommendation;
- Deal with a variety of Big Data sources including transactional, web, text, social media, and stream sensory sources.
Career Opportunities
- Big Data engineers;
- Big Data Architects
- Big Data Analyst
- Digital Transformation engineer;
- Big Data Consultant
- Big Data Project manager
Who can apply
Bachelor or equivalent in:
- Software Engineering or related discipline;
- General Business/Management with minor in CS;
Candidates from Moroccan Universities with a three-year degree (License) in Mathematics and/or Computer Science, are eligible to apply, but if admitted, they will be required to take and pass an additional online foundation offered by Al Akhawayn University partners.
Structure of the Program
30 SCH, including 15SCH of CS Courses, 9SCH Multidisciplinary (MGT and HUM) Courses, and a 6SCH Master Project.
Prerequisites
The undergraduate foundation courses required for the MSBDA are the equivalent of:
- CSC 3326 Database Systems,
- CSC 3351 Operating Systems,
- CSC 3315 Analysis of Algorithms,
- MTH 3301 Engineering Probability and Statistics or EGR 3401 Statistics for Engineers.
Key Courses
- Big Data: introduction, environment, and applications
- Descriptive Statistics
- Data mining and Machine Learning
- Data Engineering and Visualization
- Web and Text Mining
The Big Data Final Project
The purpose of the professional project is to develop and demonstrate professional competence through the application of learned tools and technologies, concepts, and techniques to build I/O or processing data pipes including Machine Learning pipes. The professional project is pursued under the close supervision of a faculty member and/or other industry/government partners with relevant expertise and is the equivalent of three months of full-time work including the report write-up.
