MSc Accounting and Financial Management
Designed for graduates from diverse academic backgrounds with quantitative training, th...
Bristol - Clifton
INTAKE: September
This intensive one-year master's program focuses on imparting a deep understanding of computational and statistical principles essential for modern data science. It emphasizes the ethical application of data analysis techniques to address real-world challenges, preparing graduates for roles as data scientists or data engineers across diverse industries.
Curriculum: The curriculum is structured to provide a blend of theoretical knowledge and practical skills. Core modules include Data Management Fundamentals, Programming for Data Science, Statistical Inference, and Machine Learning and Predictive Analytics. Students also engage in a Data Science mini-project, a group activity often aligned with external clients, fostering collaboration and real-world problem-solving abilities.
Research Focus: The University of Bristol is renowned for its research excellence, with 94% of its research assessed as world-leading or internationally excellent. The MSc Data Science program is closely associated with this research strength, ensuring that teaching is informed by the latest advancements in the field. Students are encouraged to engage in research projects that contribute to the evolving landscape of data science.
Industry Engagement: Recognizing the importance of practical experience, the program has been co-designed with industrial partners to align with current market needs. Students have opportunities to work on live data science projects, often in collaboration with industry partners, allowing them to apply their skills to real-world datasets and challenges. This collaboration enhances employability and ensures that graduates are well-prepared to meet industry demands.
Global Perspective: The University of Bristol attracts a diverse student body from over 150 countries, fostering a rich cultural exchange and a global perspective on data science challenges. The program incorporates international case studies and offers opportunities for students to work on projects with a global scope, preparing them to operate effectively in an interconnected world.
Bristol - Clifton
IELTS:6.5
£ 35500
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 Bristol offers a range of scholarship opportunities to both domestic and international students.
Vice-Chancellor’s Scholarship: This scholarship is offered to high-achieving students who are starting their undergraduate or postgraduate studies at the University of Bristol. The scholarship covers full tuition fees and a maintenance allowance.
Think Big Scholarship: This scholarship is awarded to international students who have demonstrated exceptional academic merit and potential.
Sanctuary Scholarship: This scholarship is awarded to asylum seekers, refugees, and their immediate family members who are seeking an undergraduate or postgraduate degree at the University of Bristol. The scholarship covers full tuition fees and a maintenance allowance.
The University of Bristol's MSc Data Science program is designed to prepare students for a range of data science careers across different industries. Graduates of the program can pursue roles in data analysis, machine learning, data engineering, data visualization, and other related fields.
Data Scientist: A data scientist uses analytical, statistical, and programming skills to collect, analyze, and interpret large datasets. They may be involved in designing experiments, building models, and creating visualizations.
Data Engineer: A data engineer is responsible for designing, building, and maintaining the systems that enable organizations to manage and analyze large amounts of data.
Machine Learning Engineer: A machine learning engineer builds and deploys systems that can learn from and make predictions on data. They are involved in building and training machine learning models, as well as deploying these models in production environments.
Data Analyst: A data analyst is responsible for collecting, analyzing, and interpreting data to help organizations make informed decisions. They may be involved in designing experiments, creating visualizations, and communicating insights to stakeholders.
Business Intelligence Analyst: A business intelligence analyst uses data to identify trends, create reports, and inform business decisions. They may work with large datasets to create dashboards, visualizations, and reports that help stakeholders understand business performance.