MSc Data Science with Artificial Intelligence

Become unstoppable. Turn Data into Insight.

The MSc Data Science with Artificial Intelligence is a conversion programme designed for graduates and professionals from numerate backgrounds who want to build a career working critically and responsibly with data — no prior formal study of data science is required. Delivered by Robert Kennedy College in exclusive partnership with the University of Salford’s School of Science, Engineering and Environment, it develops the computational, statistical and analytical capabilities needed to manage, analyse, model, visualise and communicate insights from complex real-world data.

You’ll bring together applied statistics and data visualisation, advanced database methods, machine learning and data mining, and big data tools and techniques — working hands-on with R, Python, SQL, Power BI, Apache Spark and MongoDB. Ethical, privacy and professional considerations run through the whole curriculum, so you learn to generate insights that are defensible as well as powerful, for technical and non-technical audiences alike.

Swiss Quality. Since 1998. British Excellence. Data Science Expertise.

This programme combines the excellence of Swiss-quality online education with the prestige of a British degree from the University of Salford. For over two decades, Robert Kennedy College has been at the forefront of online education, while the University of Salford’s School of Science, Engineering and Environment — with its research-led expertise in data science, machine learning and artificial intelligence — ensures you graduate with a globally recognised and respected qualification.

Why This Programme?

  • Conversion Route: Open to graduates of any discipline with mathematical aptitude — no computing degree required
  • Complete Data Science Toolkit: R, Python, SQL, Power BI, Apache Spark and NoSQL databases, all taught hands-on
  • From Statistics to AI: Applied statistics, visualisation, databases, machine learning and big data in a single coherent pathway
  • Fast and Flexible: Complete in as little as 9 months, 100% online via OnlineCampus, in focused six-week module blocks
  • Optional Residential Week: One week in Zürich or Salford, Manchester, to prepare your final project — or take the same workshops online

Your MSc Data Science with Artificial Intelligence degree is:

  • Recognised worldwide by employers and industry leaders
  • Awarded directly by the University of Salford
  • Identical to degrees earned on campus
  • Fully recognised by the UK government

Career Outcomes

Graduates are prepared for roles such as:

  • Data Scientist
  • Data Analyst
  • Business Intelligence Analyst
  • Machine Learning Engineer
  • Data Engineer
  • Analytics Consultant
  • Data Visualisation Specialist
  • Head of Data and Analytics
Duration

9 months to 4 years

Delivery Method

100% online via OnlineCampus (an interactive online learning environment) with intensive class discussion and collaboration.

Terms

We offer rolling admissions throughout the year. Register at any time and begin your learning journey immediately.

Tuition Fees

Full details and currency options are listed on our Tuition Plans & Rates page.

Programme not eligible for UK Government student finance.

Optional residential week

Zürich, Switzerland or Salford, Manchester

Your degree is fully achievable online. But before you begin your final project, you can choose to spend one week with fellow students and faculty - at Robert Kennedy College in Zürich, Switzerland, or on campus at the University of Salford in Manchester, England.

The residential week is built around your Project for MSc. Through workshops, supervisor sessions and peer discussion you will sharpen your research question, settle your methodology, plan your project timeline and leave with a clear roadmap for the dissertation stage. It is also a rare opportunity to meet in person the international cohort you have been studying alongside online, and to experience the two institutions behind your degree.

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Admission Requirements

We welcome applications from students who may not meet the formal entry criteria but who have relevant experience or the ability to pursue the course successfully.

The formal entry requirements are:

  • An honours degree at 2:2 or above in a Computing or closely-related discipline
  • English language at IELTS 6.0 (minimum of 5.5 in each component)

Applications are considered from candidates who do not meet the formal entry requirements but can provide evidence of equivalence.

Examples of equivalence are:

  • A wide range of professional qualifications and/or work experience
  • Working or studying in English or an English-speaking environment

Admissions interview

All applicants are interviewed by a Robert Kennedy College admissions interviewer before an offer is made. Equivalence is assessed at the interview, and offers are made in line with the admissions requirements of the University of Salford.

Programme Outline

Introductory

Not-for-credit

  • Induction

This is the first module of the programme which gives an orientation to the course and the online learning style. It does not carry credits, and students are encouraged to go through the material in this module at their own pace and get accustomed to the online medium.

The MSc Data Science with Artificial Intelligence consists of 180 credits delivered through five modules. All taught modules are core and delivered online in focused six-week blocks:

Stage 1: Taught Modules (120 credits)

  • Module 1: Applied Statistics and Data Visualisation (30 credits)
  • Module 2: Machine Learning and Data Mining (30 credits)
  • Module 3: Advanced Databases (30 credits)
  • Module 4: Big Data Tools and Techniques (30 credits)

Stage 2: Project for MSc (60 credits)

Module 5: Project for MSc (Dissertation) (60 credits)

Exit awards: PgCert / PgDip Data Science (International) are available for students who complete 60 or 120 credits respectively.

Module Descriptions

Module 1: Applied Statistics and Data Visualisation (30 credits)

  • Descriptive and inferential statistics and probability distributions
  • Hypothesis testing, ANOVA, regression and time series analysis
  • Solving statistical problems using R
  • Theory and practice of data visualisation
  • Dashboards, reports and data stories in Power BI

Module 2: Machine Learning and Data Mining (30 credits)

  • The full data mining lifecycle, from data preprocessing to exploratory analysis
  • Supervised and unsupervised algorithms: association rules, clustering and classification
  • Neural networks, ensemble methods and text mining
  • Practical activities in Python to extract and interpret insights from data
  • Ethical and societal implications of machine learning practice

Module 3: Advanced Databases (30 credits)

  • Relational database design and normalisation
  • Advanced SQL querying and data types
  • Indexing, recovery, security and transaction management
  • Distributed databases, parallel systems and large-scale analytics
  • How current research shapes the practical deployment of big data systems

Module 4: Big Data Tools and Techniques (30 credits)

  • Defining characteristics, challenges and opportunities of Big Data
  • Cloud computing, distributed processing frameworks and NoSQL databases
  • Ingesting, processing, analysing and storing massive datasets
  • Hands-on Apache Spark, PySpark and MongoDB on real-world text, image and IoT sensor data
  • Machine learning and recommender systems at scale

Module 5: Project for MSc (Dissertation) (60 credits)

  • Independent, research-informed project on a substantive problem in your field
  • Robust research proposal and critical review of current practice and the state of the art
  • Ethical considerations and appropriate methodologies and technologies
  • A 15,000-word dissertation with results, reflections and recommendations
  • Supported throughout by a dedicated supervisor