MSc in Big Data & Business Analytics
DURATION
18 Months
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
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EARLIEST START DATE
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TUITION FEES
EUR 13,500 / per year
STUDY FORMAT
On-Campus
Introduction
Big Data Analytics has emerged as a discipline that emphasizes the development of advanced data-driven computer programs that can access data around the globe. Data analytics tools, techniques, and a multitude of techniques have provided businesses with alarming ways to analyze data and unravel insights. Big data analytics has emerged as a clever clog to analyze this varied and magnanimous data. This has served as a boon to businesses as it enables them to rummage informed decisions out of the data pile.
Big data analytics comprises advanced analytics involving intricate applications of statistical, and mathematical concepts in conjunction with advanced algorithms. This upbeat and hands-on style to reach business decisions is transformative because it empowers decision-makers with the power to make informed decisions to approach real-time business objectives.
The MSc program in Big Data & Business Analytics would allow students to gain an understanding of the various data sources and enable them to study, understand and analyze the data incurred across sources. This program in big data analytics follows a multi-disciplinary approach at its center, focusing on the prevalent as well as evolving Big Data tools such as Hadoop and Cloud Architecture.
This program is everything one would need to make an effective career shift and delve into the world of big data analytics.
Students will discover the concepts and gain expertise in the usage and applications of algorithms of Big Data Analytics. They will have abundant opportunities to plunge into advanced concepts.
Through hands-on projects, students will gain experience with the concepts behind search algorithms, clustering, classification, optimization, reinforcement learning, and other topics and incorporate the learning in R Programs.
This program enables students to embrace the concepts of Big Data and understand their extension to its application. Students work on projects involving the development of facial recognition systems and manipulation.
Every student of ESDST is assisted by an industry-specific mentor. A mentor is responsible for guiding the students through the courses and offering them experiential and core learning with real-life examples.
After the end of this program students will be able to:
- Demonstrate an understanding of Big Data and its analytics in the real world
- Apply the conceptual framework of Big Data Analytics and problem-solving techniques.
- perform data gathering of large data from a range of data sources.
- Critically analyze existing Big Data datasets and implementations, taking practicality, and usefulness metrics into consideration.
- Employ advanced statistical analytical skills to test assumptions, and to generate and present new information and insights from large datasets
- Recommend solutions by applying advanced knowledge of statistical data analytics to large data sets
- Analyze the Big Data framework like NOSQL to efficiently store and process Big Data to generate analytics
Admissions
Curriculum
Courses
- Business Statistics and Advanced Excel (4 ECTS)
- Business Analytics and Research Methods Foundation (4 ECTS)
- Programming for Analytics using Python (4 ECTS)
- Predictive Analytics Methods (4 ECTS)
- Business Communication (3 ECTS)
- Professional Career Lab (1 ECTS)
- Big Data and NoSQL (4 ECTS)
- Apache Pig, Apache Hive and Zookeeper (4 ECTS)
- Spark Programming (4 ECTS)
- Data Warehousing and Management (4 ECTS)
- Ethics in Data Management (4 ECTS)
- MapReduce Programming (5 ECTS)
- Natural Language Processing (5 ECTS)
- Artificial Intelligence and Machine Learning (5 ECTS)
- Data Visualization and Storytelling with Tableau (5 ECTS)
- Econometrics (5 ECTS)
- Business Application Seminar (5 ECTS)
- Spanish Language (10 ECTS)
- Master Thesis (20 ECTS)
- Internship (20 ECTS)
Total ECTS Credits: 90
Career Opportunities
After successful completion of the program, career roles would be guided by the level of expertise of the students and prior experience. Some job titles that can be explored include:
- Big Data Analyst
- Business Intelligence Manager
- Data Scientist
- Predictive Analytics Specialist
- Business Analytics Consultant
- Quantitative Analyst
- Market Research Analyst
- Data Analytics Manager
- Chief Data Officer (CDO)
- Financial Data Analyst
Accreditations
Program Admission Requirements
Show your commitment and readiness for Grad school by taking the GRE - the most broadly accepted exam for graduate programs internationally.