MSc Business & Management (MBM)
The MSc Business & Management program at the University of Strathclyde is designed ...
BSc (Hons) Data Analytics
Glasgow
INTAKE: September
Program Overview
The University of Strathclyde in the UK offers an esteemed undergraduate program, BSc (Hons) Data Analytics, tailored to equip students with the skills and knowledge needed to thrive in the rapidly evolving field of data science. This program provides a comprehensive understanding of data analysis techniques, statistical methods, and computational tools essential for extracting insights from large datasets. Students explore various aspects of data analytics, including data visualization, machine learning, and data-driven decision-making, preparing them for rewarding careers in data-driven industries such as finance, healthcare, and technology.
Curriculum: The BSc (Hons) Data Analytics curriculum at the University of Strathclyde is designed to cover a wide range of topics essential for data analysts and data scientists. Students study modules such as statistical analysis, programming languages (e.g., Python, R), database management, machine learning, and data visualization. The curriculum emphasizes hands-on experience through practical projects, case studies, and industry-relevant assignments, allowing students to develop proficiency in data manipulation, analysis, and interpretation using state-of-the-art tools and techniques.
Research Focus: Research forms a significant component of the BSc (Hons) Data Analytics program at the University of Strathclyde, with a focus on advancing knowledge in data science and contributing to innovative solutions for real-world problems. Students have the opportunity to engage in research projects that explore emerging trends in data analytics, such as predictive modeling, natural language processing, or deep learning. Faculty members are actively involved in research, collaborating with industry partners and academic institutions to address challenges in data analysis and develop cutting-edge methodologies.
Industry Engagement: The BSc (Hons) Data Analytics program emphasizes industry engagement and practical experience to prepare students for the demands of the data-driven job market. The University of Strathclyde has strong connections with leading companies and organizations in sectors such as finance, healthcare, retail, and technology, providing students with internship opportunities, industry placements, and guest lectures from industry experts. Students also have access to networking events, career fairs, and professional development workshops to enhance their employability and establish connections with potential employers in the field of data analytics.
Global Perspective: The University of Strathclyde promotes a global perspective in the BSc (Hons) Data Analytics program by exploring data analytics within a global context and addressing challenges and opportunities in a diverse range of industries and geographical regions. Students examine case studies and examples from around the world, gaining insights into the application of data analytics in different cultural, economic, and regulatory environments. Study abroad opportunities, international research collaborations, and multicultural learning experiences further enrich students' global perspective, preparing them to work in multinational organizations and tackle global data challenges.
Location
Glasgow
Score
IELTS 6.5
Tuition Fee
£ 17400
Undergraduate Entry Requirements
Academic Qualifications: Applicants should have successfully completed their secondary education with a minimum overall score of 70 to 75% or equivalent in their respective country's grading system.
English language proficiency:
- IELTS: A minimum overall score of 6.5 with no individual component below 5.5.
- TOEFL: A minimum overall score of 90, with at least 19 in Listening, Reading, Speaking, and Writing.
- PTE Academic: A minimum overall score of 62 with no individual score below 51.
- 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 Strathclyde offers a range of scholarships and financial aid options to support students in their academic journey. These scholarships are designed to recognize excellence, provide access to education, and support students in pursuing their goals.
Excellence Scholarship: The Excellence Scholarship is awarded to high-achieving students entering undergraduate programs at the University of Strathclyde. It provides a financial contribution towards tuition fees and is available for both Scottish and international students.
Faculty-specific Scholarships: Many faculties within the University of Strathclyde offer scholarships tailored to specific areas of study. These scholarships aim to attract exceptional students and provide them with financial support throughout their academic program.
International Undergraduate Scholarship: This scholarship is available to international undergraduate students who have demonstrated academic excellence. It offers a financial award towards tuition fees and is renewable for subsequent years based on satisfactory academic progress.
Graduates of the BSc (Hons) Data Analytics program at the University of Strathclyde are well-prepared for a wide range of exciting career opportunities in the rapidly growing field of data science.
Data Analyst: Graduates can work as data analysts, responsible for collecting, cleaning, and analyzing data to extract meaningful insights and inform decision-making processes. They use statistical techniques, data visualization tools, and programming languages to interpret data and identify trends, patterns, and correlations.
Data Scientist: Graduates can pursue careers as data scientists, leveraging advanced analytical skills and machine learning algorithms to solve complex problems and develop predictive models. They work on projects such as predictive analytics, recommendation systems, and natural language processing, using big data technologies and programming languages like Python and R.
Business Intelligence Analyst: Graduates can work as business intelligence analysts, supporting organizations in making data-driven decisions by transforming raw data into actionable insights. They develop dashboards, reports, and data visualizations to communicate key performance indicators (KPIs) and business metrics, helping stakeholders understand trends and opportunities.
Machine Learning Engineer: Graduates with a strong background in machine learning can pursue careers as machine learning engineers, designing and implementing machine learning algorithms and models to solve specific business problems. They collaborate with cross-functional teams to deploy machine learning solutions and optimize model performance.
Data Engineer: Graduates can work as data engineers, responsible for designing, building, and maintaining data infrastructure and pipelines to support data analysis and machine learning initiatives. They work with databases, data warehouses, and cloud computing platforms to ensure data availability, reliability, and scalability.
Quantitative Analyst (Quant): Graduates interested in finance can pursue careers as quantitative analysts, applying mathematical and statistical techniques to analyze financial markets, develop trading strategies, and manage investment portfolios. They work for hedge funds, investment banks, and financial institutions, using data analytics to make informed investment decisions.
Healthcare Data Analyst: Graduates can specialize in healthcare analytics, working for hospitals, healthcare providers, or pharmaceutical companies to analyze clinical data, optimize healthcare delivery, and improve patient outcomes. They apply data analytics techniques to identify trends, monitor healthcare performance, and inform healthcare policy and planning.
Marketing Analyst: Graduates can work as marketing analysts, supporting marketing teams in understanding customer behavior, measuring campaign effectiveness, and optimizing marketing strategies. They analyze customer data, conduct market research, and use predictive analytics to identify target audiences and personalize marketing campaigns.
Consultant: Graduates can work as data analytics consultants, providing advisory services to organizations seeking to leverage data for strategic decision-making and competitive advantage. They assess data capabilities, develop analytics strategies, and implement data-driven solutions to address business challenges and opportunities.
Research Scientist: Graduates interested in research can pursue careers as research scientists, working in academia, research institutes, or private sector research labs. They conduct research in areas such as data mining, artificial intelligence, and computational statistics, contributing to scientific advancements and innovation in data analytics.
