MSc Applied Data Science (Degree Apprenticeship)

Program Overview

This 21-month blended learning program trains working professionals to become competent data scientists. It combines academic rigor with hands-on experience, focusing on advanced technical skills, leadership capabilities, and responsible data practices. Graduates are prepared for careers in data science, data analysis, and other data-driven roles across industries. The program is designed to upskill or reskill individuals and drive business transformation through data.

Program Outline

Degree Overview:

Objectives:

• Train apprentices to become competent data scientists who can deliver strategic data-driven solutions.
• Develop expertise in data mining, machine learning, leadership, and ethical data practices.
• Equip graduates with the skills needed to lead teams and drive business transformation through data.

Description:

• 21-month program designed for working professionals with a desire to upskill or reskill.
• Blended learning format with live online sessions and in-person training workshops.
• Combines academic rigor with hands-on experience through applied projects and dissertations.
• Focus on advanced technical skills, leadership capabilities, and responsible data practices.

Outline:

Program Content:

• Data Science Fundamentals (Mathematics, Statistics, Scripting)
• Research Methodology and Academic Writing
• Data Analysis and Exploration Techniques
• Applied Data Mining and Machine Learning Algorithms
• Data Visualization and Communication Strategies
• Data-Driven Leadership and Business Transformation
• Responsible Data Practices and Ethical Considerations

Program Structure:

• Taught Modules (e.g., Research Methods, Data Mining, Leadership & Innovation)
• Dissertation - Investigating and solving real-world data science problems in the workplace
• Individual Project - Applying learned skills to a complex business problem

Module Descriptions:

• Research Methods (RMET): Develop research and academic skills necessary for successful postgraduate study.
• Applied Techniques of Data Mining and Machine Learning (DMML): Explore fundamental concepts, basic and advanced techniques in data mining and machine learning.
• Systems and Tools for Data Science (STDS): Learn and apply leading software tools and platforms used in data science projects.
• Leadership and Innovation in Data Science (LIDS): Develop inclusive leadership skills, cultural awareness, and ethical data governance principles.
• Work-based Dissertation (WBDS): Apply research skills to investigate and recommend data-driven solutions for organizational objectives.
• Degree Apprenticeship Project (DAPR): Deep dive into a specific data science area, solve complex problems using acquired knowledge and skills.

Assessment:

• Continuous assessment throughout the program through assignments, presentations, projects, and examinations.
• Apprentices must achieve a pass in all modules and the final dissertation to receive the MSc degree.
• The apprenticeship component includes an End-Point Assessment (EPA) conducted by an independent organization to evaluate workplace competencies and skills acquired.

Teaching:

• Experienced and research-active academics with strong industry experience.
• Interactive learning environment with small class sizes, live online sessions, and in-person workshops.
• Opportunity to benefit from guest lectures by leading industry experts.

Careers:

• Graduates are prepared for careers as Data Scientists, Data Analysts, Machine Learning Engineers, AI Specialists, Business Intelligence Consultants, and other data-driven roles across industries.
• Many alumni secure promotions or transition to new opportunities within the data science field.

Other:

• The University of Buckingham offers high-quality, small-group teaching with globally recognized qualifications.
• The curriculum is constantly reviewed and updated based on industry feedback, external examiners, and staff research.
• Students have access to a comprehensive library, online journals, databases, and software resources.
• The University hosts Computing seminars throughout the year, covering cutting-edge research topics.

Note:

• Admission criteria and program fees are not included in this extraction as they fall outside the scope of the requested sections.

Apprenticeships are fully funded by the employer through the Apprenticeship Levy. The maximum cost for the L7 DTSS Integrated Degree Apprenticeship is £21,000; this may be less dependent on your Recognised Previous Learning (RPL) which will be assessed at interview through a robust initial skills assessment.