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1 Years On Campus Masters Program
Anglia Ruskin University Cambridge CampusThe MSc Applied Data Science at Anglia Ruskin University provides practical training in statistics, machine learning, programming and real-world data analysis. It suits graduates from any discipline who want to transition into data science or analytics with hands-on, industry-focused skills.
Curriculum structure
Students begin with Analytical Techniques and Programming with Python, gaining essential foundations in statistics, mathematical reasoning, coding and data handling. They then progress to Principles of Data Mining and Machine Learning and Applied Data Analysis and Research Methodology, learning to build predictive models, extract patterns from data and apply analytical methods to real datasets. The programme concludes with the Data Analytics Major Project and Placement, where students complete an applied data-science project or industry placement to build a professional portfolio.
Focus areas: “Statistics, Python Programming, Data Mining, Machine Learning, Applied Data Analysis, Real-World Projects”
Learning outcomes: “Clean and process data; build ML/statistical models; interpret and visualise analytical results; apply data-science methods to real problems; complete an industry-aligned project.”
Professional alignment (accreditation): Prepares graduates for roles in data science, analytics, business intelligence, tech, finance, healthcare and research.
Reputation (employability rankings): ARU is known for practical, career-oriented computing and analytics programmes, supporting strong employability in data-driven sectors.
Students develop applied data science skills by working directly with real-world datasets using advanced analytics software and high-performance computing infrastructure. This practical focus ensures proficiency in extracting insights and building predictive models.
The experiential components are structured through specific facilities and projects:
Software & Tools: Industry-standard analysis using Python (Pandas, Scikit-learn, TensorFlow/PyTorch), R, SQL, and Tableau, managed within environments like Jupyter Notebooks and Git.
Computing Infrastructure: Access to high-performance computing (HPC) resources and dedicated data science labs for processing large, complex datasets.
Group Project: A core collaborative data science project where students work in teams to solve an authentic business or research problem, covering the full data lifecycle from acquisition to visualisation.
Applied Research: Opportunities to engage with real-world challenges through the university's Computing, Informatics and Applications Research Group (CIARG) and dissertation projects often linked to industry or academic research problems.
Graduates of Anglia Ruskin University's MSc Applied Data Science master advanced machine learning, predictive analytics, data mining, and AI tools, enabling them to drive data-driven innovation across finance, healthcare, technology, and social care sectors. Real-world projects and industry datasets build practical expertise for high-impact roles amid surging demand for data professionals. Typical job roles: data scientist, machine learning engineer, data analyst, business intelligence specialist.
University services: Careers service with CV workshops, employer networking, and Major Project placement opportunities enhance employability.
Employment stats/salary: Top 15% UK employment rates; 75% earn ≥£24k within 15 months (many ≥£44k).
University–industry partnerships: Real datasets and simulated projects with business/healthcare partners.
Long-term accreditation value: Skills in deep learning/AI ensure adaptability to evolving data challenges.
Graduation outcomes: Roles in tech, finance, healthcare analytics worldwide.
Further Academic Progression: Pursue PhD Data Science at ARU, extending Major Project research.
A first degree, with honours, at a minimum final classification of Lower Second (2:2) or equivalent.India- 3 year Bachelors or 4 year Bachelor Engineering or Technology, minimum division 2 (50% - 59%) in relevant subjectsUSA- Bachelor degree with final GPA of 2.7IELTS (Academic) Overall 6.5 with 5.5 in each of the four language skills (listening, speaking, reading and writing)TOEFL iBT 88 overall with 17 in Writing and Listening, 18 in Reading and 20 in Speaking Data ScientistsData AnalystsMachine Learning EngineersBusiness Intelligence Analystsand Data Engineersacross financehealthcareretailtechnologyand public sector organisations
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