MSc International Relations
The MSc International Relations program at the University of East London is designed to...
London
INTAKE: Jan, May & Sept
The MSc Big Data Technologies program at the University of East London (UEL) is a cutting-edge postgraduate course that equips students with the skills and knowledge needed to excel in the rapidly evolving field of big data.
Program Structure: The MSc Big Data Technologies program typically spans one year of full-time study or two years part-time. It is designed to provide a comprehensive understanding of big data technologies and their applications.
Core Modules: The program includes a set of core modules that cover essential aspects of big data, such as data analytics, data management, machine learning, and data visualization. These modules build a strong foundation in big data technologies.
Cutting-Edge Technologies: Students are exposed to the latest tools and technologies used in the field of big data, including Hadoop, Spark, Python, and data warehousing systems. Practical hands-on experience is emphasized.
Data Science Skills: The program focuses on developing data science skills, including data preprocessing, data modeling, and predictive analytics. Students gain the ability to extract valuable insights from large and complex datasets.
Real-World Projects: Many MSc programs in big data include real-world projects or case studies. These projects provide students with the opportunity to apply their knowledge to practical scenarios and industry challenges.
Big Data Ethics: An ethical dimension is often integrated into the curriculum, addressing the responsible use of data and privacy concerns.
Industry Partnerships: Some programs have partnerships with industry leaders, allowing students to benefit from guest lectures, internships, and networking opportunities with professionals in the big data sector.
Research Component: Many MSc programs require students to undertake a research project or dissertation in the field of big data. This research component allows students to explore a specific area of interest in depth.
London
IELTS 6.5
£ 15240
Postgraduate Entry Requirements:
Students must provide:
Work experience: Some postgraduate courses may require relevant work experience in the field.
It is important to note that meeting the minimum entry requirements does not guarantee admission, as the university considers factors such as availability of places and competition for the program. Additionally, some courses may have higher entry requirements or additional selection criteria, such as interviews or portfolio submissions.
The University of East London (UEL) is committed to providing financial support to international students through a range of scholarship opportunities. These scholarships are designed to recognize academic excellence, promote diversity, and help deserving students pursue their educational goals.
It is important to note that scholarship availability, eligibility criteria, and application deadlines may vary each year.
Graduates of the MSc Big Data Technologies program at the University of East London (UEL) are well-prepared for a wide range of career opportunities in the burgeoning field of big data.
Data Analyst: Graduates can work as data analysts, using their skills to analyze and interpret data for organizations across various industries.
Data Scientist: Opportunities exist in data science roles, involving the development of predictive models and data-driven strategies.
Big Data Engineer: Graduates may pursue careers as big data engineers, responsible for designing and maintaining data infrastructure.
Business Intelligence Analyst: Some graduates choose roles as business intelligence analysts, assisting organizations in making data-informed decisions.
Machine Learning Engineer: With a strong foundation in machine learning, graduates can contribute to the development of machine learning models and algorithms.
Data Consultant: Graduates may work as data consultants, helping businesses leverage big data to solve complex problems and gain a competitive edge.
Researcher or Academic: Opportunities exist in research and academia, contributing to advancements in big data technologies and applications.