MSc

MSc Data Science

Turn data into decisions that matter

Online or on campus

24 months36 creditsEnglish

Overview

Data science sits at the intersection of statistics, computing, and domain expertise. This programme teaches you to frame business questions as analytical problems, wrangle messy real-world datasets, and communicate findings to non-technical audiences. Modules cover Bayesian inference, deep learning, NLP, and MLOps. You will work with public datasets from healthcare, finance, and climate science, building a portfolio that demonstrates end-to-end analytical capability.

Every module uses real datasets — never toy CSVs alone. You will document reproducible notebooks and present to a mock executive panel in the capstone. Frontier partners with public-health NGOs for anonymised analytics projects.

Who This Program Is For

Analysts upgrading from Excel to Python and ML workflows
Engineers moving into ML engineering or analytics engineering
Researchers needing formal statistical and computing credentials

Faculty spotlight

Dr. Priya Sharma, ex-lead data scientist at a global bank, teaches MLOps; Professor Daniel Mensah specialises in causal inference for policy evaluation.

How you can study

Study options & delivery

Online pathway· Flexible remote

Complete your MSc Data Science fully online from anywhere in the world with faculty-led modules and flexible scheduling.

On-campus pathway· £4,100 / $5,200/year

Attend seminars and access facilities in person at Frontier Innovation University.

Apply online →Apply for campus →View fee schedule

What You Will Learn

Apply statistical inference and experimental design to business problems
Build and validate predictive models using scikit-learn, PyTorch, and R
Design dashboards and narratives that drive executive action
Implement reproducible data pipelines with version control and testing
Evaluate AI systems for fairness, bias, and regulatory compliance
Design A/B tests and interpret results for product and policy teams
Document model cards and monitoring plans for production ML

Curriculum

Year 1 — Foundations

Code	Course	Credits
DS501	Statistics & Probability for Data Science Statistics & Probability for Data Science — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in Statistics & Probability for Data Science Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3
DS502	Programming for Analytics (Python/R) Programming for Analytics (Python/R) — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in Programming for Analytics (Python/R) Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3
DS503	Data Wrangling & SQL Data Wrangling & SQL — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in Data Wrangling & SQL Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3
DS504	Data Visualisation & Storytelling Data Visualisation & Storytelling — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in Data Visualisation & Storytelling Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3

Year 1 — Modelling

Code	Course	Credits
DS505	Machine Learning Fundamentals Machine Learning Fundamentals — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in Machine Learning Fundamentals Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3
DS506	Deep Learning & Neural Networks Deep Learning & Neural Networks — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in Deep Learning & Neural Networks Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3
DS507	Natural Language Processing Natural Language Processing — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in Natural Language Processing Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3
DS508	Time Series & Forecasting Time Series & Forecasting — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in Time Series & Forecasting Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3

Year 2 — Applied

Code	Course	Credits
DS601	MLOps & Production Systems MLOps & Production Systems — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in MLOps & Production Systems Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3
DS602	Big Data Technologies (Spark) Big Data Technologies (Spark) — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in Big Data Technologies (Spark) Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	3
DS603	MSc Data Science Capstone MSc Data Science Capstone — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway. Core concepts and frameworks in MSc Data Science Capstone Theory applied to contemporary organisational cases Methods, tools, and professional standards Ethics, risk, and responsible practice Assessment: coursework, exam, or applied project	6

Code

Course

Credits

DS601

MLOps & Production Systems

MLOps & Production Systems — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway.

Core concepts and frameworks in MLOps & Production Systems
Theory applied to contemporary organisational cases
Methods, tools, and professional standards
Ethics, risk, and responsible practice
Assessment: coursework, exam, or applied project

DS602

Big Data Technologies (Spark)

Big Data Technologies (Spark) — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway.

Core concepts and frameworks in Big Data Technologies (Spark)
Theory applied to contemporary organisational cases
Methods, tools, and professional standards
Ethics, risk, and responsible practice
Assessment: coursework, exam, or applied project

DS603

MSc Data Science Capstone

MSc Data Science Capstone — core module covering foundational concepts, applied practice, and formal assessment on this degree pathway.

Core concepts and frameworks in MSc Data Science Capstone
Theory applied to contemporary organisational cases
Methods, tools, and professional standards
Ethics, risk, and responsible practice
Assessment: coursework, exam, or applied project

Career Paths

Data Scientist
Analytics Engineer
Business Intelligence Lead
Quantitative Research Analyst
AI Product Manager

Program Highlights

Kaggle-style team competitions with industry datasets
Python, R, and SQL proficiency by graduation
Ethics module aligned with EU AI Act principles
Partnership projects with NGO and public-sector data
Pathway to PhD for high-performing graduates
Ethics module aligned with UK GDPR and EU AI Act literacy
Pathway to PhD for distinction-level capstone projects

Assessment

Modules are assessed through a published mix of coursework, applied projects, and examinations. Exam windows are announced in advance so students in other time zones are not forced into overnight sittings. Alternative arrangements are available where documented.

Admission requirements

Academic entry

Bachelor's degree from an accredited institution (minimum 2:2 or GPA 2.5/4.0)

English language

English proficiency: IELTS 5.5, TOEFL 46, or equivalent (waived for prior English-medium study)

Documents

Statement of Purpose (500 words minimum) outlining your goals and fit for the programme
Two academic or professional references with contact details

Programme questions

How long is the MSc Data Science?

The published duration is 24 months. Teaching language: English. Actual time-to-complete depends on mode and any recognised prior learning.

Can I study this from my country?

You may study this award fully online from your country, or — where published — on campus at Frontier. Online study does not require a student visa. Campus study may.

What does it cost?

Online awards at Frontier Innovation University are published at about $600–$900 in total, paid by semester ($200–$400) after you accept an offer. The online application fee is $0. Exam and administrative charges may apply. See Fees for the current table.

What are the entry requirements?

Requirements are grouped on this page (academic, English, documents). Equivalent qualifications are considered. English may be waived after prior English-medium study.

How is the programme assessed?

Assessment is typically a mix of coursework, projects, and examinations. Doctoral awards include a thesis or dissertation and an oral examination. Details sit in the programme specification and module outlines.

Will this award be recognised where I live?

Recognition of the award for local employment, professional licence, or ministry attestation is decided by your employer or regulator. Frontier Innovation University publishes verification pages for certificates. We do not claim automatic equivalence in every country.

How do I apply?

Start an application on this website. Progress is saved from the first step. Admissions: admissions@frontuni.com.

Recognized & Accredited

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