MSc Accounting and Finance
The MSc Accounting and Finance program at the University of Greenwich is designed to pr...
BSc Hons Computer Science (Data Science)
Greenwich Campus
INTAKE: September
Program Overview
The BSc (Hons) Computer Science (Data Science) program at the University of Greenwich, UK, is designed to equip students with the knowledge and skills necessary to navigate the rapidly evolving field of data science. This undergraduate degree program provides students with a comprehensive understanding of computer science fundamentals, data analysis techniques, and machine learning algorithms, preparing them for careers in data-driven industries.
Curriculum: The curriculum of the BSc (Hons) Computer Science (Data Science) program covers a wide range of topics essential for understanding data science principles and practices. Courses typically include modules on programming languages such as Python and R, data visualization, statistical analysis, machine learning, big data technologies, and data ethics. The program also incorporates practical components, such as data analysis projects, case studies, and internships, to provide students with hands-on experience in applying data science techniques to real-world problems.
Research Focus: The University of Greenwich emphasizes a strong research focus within the BSc (Hons) Computer Science (Data Science) program. Faculty members are actively engaged in research projects exploring various aspects of data science, including data mining, predictive modeling, natural language processing, and artificial intelligence. Students have the opportunity to participate in research initiatives, allowing them to gain practical research skills and contribute to advancing knowledge in the field through independent research projects and dissertation work.
Industry Engagement: The BSc (Hons) Computer Science (Data Science) program prioritizes industry engagement to ensure that students are well-prepared for the demands of the professional world. Through partnerships with technology companies, research institutes, and government agencies, students have the opportunity to gain practical experience through internships, placements, and collaborative projects. These industry connections enable students to develop professional skills, build networks, and enhance their employability upon graduation.
Global Perspective: In an increasingly interconnected world, understanding global trends, challenges, and opportunities in data science is essential for addressing complex problems and driving innovation. The BSc (Hons) Computer Science (Data Science) program at the University of Greenwich incorporates a global perspective into its curriculum. Students explore topics such as cross-cultural data analysis, global data privacy regulations, and international applications of data science. Additionally, the program may offer opportunities for students to study abroad or engage in international research projects to gain exposure to diverse cultural and technological contexts.
Location
Greenwich Campus
Score
IELTS 6.5
Tuition Fee
£ 16150
Undergraduate Entry Requirements
Academic Qualifications: Applicants should have successfully completed their secondary education with a minimum overall score of 70% or equivalent in their respective country's grading system.
English language proficiency:
- IELTS: A minimum overall score of 6.0 or 6.5 with no individual component below 5.5.
- TOEFL: A minimum overall score of 87, with at least 17 in Listening, Reading, Speaking, and Writing.
- PTE Academic: A minimum overall score of 76 with no individual score below 59.
- Some programs may have specific subject prerequisites or additional requirements.
Students must provide:
- academic marksheets & transcripts
- letters of recommendation
- a personal statement - SOP
- passport
- other supporting documents as required by the university.
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 Greenwich offers a range of scholarships and financial support options to assist students in their academic journey. These scholarships are designed to recognize academic excellence, support talented students, and provide financial assistance to those who need it.
Vice-Chancellor's Scholarship: This scholarship is available to high-achieving undergraduate and postgraduate students who demonstrate academic excellence. It provides a tuition fee discount of up to £5,000.
International Scholarship: The International Scholarship is aimed at international students applying for undergraduate or postgraduate programs at the University of Greenwich. It offers a tuition fee discount of up to £3,000.
Greenwich Scholarship Programme: The Greenwich Scholarship Programme is open to UK and EU undergraduate students from low-income backgrounds. It offers financial support in the form of bursaries and scholarships, with values ranging from £500 to £2,000 per year.
Sports Scholarships: The university provides Sports Scholarships to talented student-athletes who excel in their chosen sport. These scholarships offer a combination of financial support, access to training facilities, coaching, and other support services.
External Scholarships:The University of Greenwich provides information and support to students who wish to apply for external scholarships, grants, and funding opportunities offered by external organizations and foundations.
Graduates of the BSc (Hons) Computer Science (Data Science) program at the University of Greenwich are well-equipped for a variety of career opportunities in the rapidly expanding field of data science. With a strong foundation in computer science fundamentals, data analysis techniques, and practical experience gained through projects and internships, graduates can pursue diverse roles aimed at extracting insights from data and solving complex problems in various industries and sectors.
Data Scientist: Data scientists are responsible for analyzing large datasets to extract meaningful insights and inform business decisions. Graduates can pursue careers as data scientists, where they use statistical analysis, machine learning algorithms, and data visualization techniques to uncover patterns, trends, and correlations in data. They may work in fields such as finance, healthcare, retail, or technology, tackling problems such as customer segmentation, predictive modeling, and recommendation systems.
Machine Learning Engineer: Machine learning engineers develop and deploy algorithms that enable computers to learn from data and make predictions or decisions. Graduates can pursue careers as machine learning engineers, where they design and implement machine learning models, optimize algorithms for performance and scalability, and integrate them into software applications or systems. They may work on projects such as image recognition, natural language processing, or autonomous vehicles.
Data Analyst: Data analysts are responsible for collecting, cleaning, and analyzing data to identify trends, patterns, and insights that inform business decisions. Graduates can pursue careers as data analysts, where they use programming languages such as Python or R, statistical techniques, and data visualization tools to analyze data and communicate findings to stakeholders. They may work in fields such as marketing, finance, operations, or research, helping organizations understand their data and make informed decisions.
Business Intelligence Developer: Business intelligence developers design and develop systems that enable organizations to gather, store, and analyze data for decision-making purposes. Graduates can pursue careers as business intelligence developers, where they design data warehouses, develop ETL (extract, transform, load) processes, and create dashboards and reports to visualize key performance indicators and business metrics. They may work with tools such as SQL, Tableau, or Power BI to deliver actionable insights to business users.
Data Engineer: Data engineers are responsible for building and maintaining the infrastructure and systems that enable the collection, storage, and processing of large volumes of data. Graduates can pursue careers as data engineers, where they design and implement data pipelines, integrate data from various sources, and ensure data quality and reliability. They may work with technologies such as Hadoop, Spark, or Kafka to support data-driven applications and analytics.
Research Scientist: Research scientists conduct research and development to advance the field of data science and contribute to new discoveries and innovations. Graduates can pursue careers as research scientists, where they work in academia, industry research labs, or government agencies, conducting research on topics such as machine learning algorithms, data mining techniques, or artificial intelligence applications. They may publish papers, present findings at conferences, and collaborate with interdisciplinary teams to solve complex problems.
