courses/MSc_Data_Science_and_Analytics (1).txt

### MSc Data Science and Analytics (Sep 25, 2025 – Sep 24, 2026)
University of Hertfordshire

This is a full-time postgraduate programme designed to equip students with cutting-edge knowledge in data science, artificial intelligence, and analytical methods. It is delivered by the School of Physics, Engineering and Computer Science at the University of Hertfordshire.

### Course Duration and Study Options
The MSc Data Science and Analytics programme is available in the following formats:
- Full-time: 1 year (from Sep 25, 2025 to Sep 24, 2026)
- Part-time: 18 months (starting in September 2025)
- With optional placement year: 2 years (from Sep 2025 to Sep 2027)
You can choose from three award routes depending on your goals:
1. MSc Data Science and Analytics
2. MSc Data Science and Analytics with Placement Year
3. MSc Data Science and Analytics with Advanced Research

### Entry Requirements and Prerequisites
To be accepted into the MSc Data Science and Analytics programme, you must meet the following criteria:
- Hold a good honours degree (2:2 or above) in Computer Science or a closely related field.
- Applicants from non-STEM backgrounds (also called Far-STEM) may be required to complete a preparatory bootcamp or demonstrate a relevant portfolio.
- English language proficiency: IELTS score of at least 6.0 overall (some cases require 6.5 or higher).
- It is also important that applicants have prior experience or familiarity with:
  - Programming in Python or R
  - Basic knowledge of SQL
  - Exposure to MATLAB or other data analysis tools

### Tuition Fees and Available Funding
The tuition fees for the 2025–2026 academic year are as follows:
- UK/Home students: approximately £8,925 to £12,360
- International students: approximately £16,450 to £17,950
Please note that there are no additional tuition fees for the optional placement year. Scholarships may also be available, such as the Chancellor’s International Scholarship and region-based funding opportunities.

### Modules and Course Structure
The course includes the following modules, amounting to 180 credits in total:
- Foundations of Data Science – 30 credits
- Neural Networks & Machine Learning – 30 credits
- Data Mining – 15 credits
- Applied Data Science & Analytics – 15 credits
- Responsible Technology – 15 credits
- MSc Project – 60 credits
Students who choose the placement route will also complete modules in Placement Preparation and Supervised Placement.

### Teaching Style and Assessment Methods
This course is delivered through a combination of lectures, seminars, and practical lab sessions using industry-standard tools. There is a strong emphasis on independent study, supported by 24/7 access to computer labs and digital learning environments like Studynet. Assessment methods include coursework, formal examinations, and a major final project.

### Learning Facilities and Student Support
Students enrolled in this programme will have access to state-of-the-art facilities in the newly developed Spectra building. These include labs focused on robotics, AI, data analytics, networking, and specialised dark rooms. You will also benefit from academic support hubs, personalised career mentoring, and access to Learning Resource Centres (LRCs) with round-the-clock availability.

### Work Placement and Career Opportunities
If you choose the placement route, you will have the option to complete a one-year paid industry placement after passing your first 60 credits. Graduates from this programme have gone on to secure roles such as:
- Data Scientist
- Data Engineer
- Analytics Consultant
- Machine Learning Engineer
- Digital Marketing Manager

### Professional Accreditation
This programme is accredited by BCS, The Chartered Institute for IT. This accreditation helps graduates meet academic requirements toward becoming a Chartered IT Professional (CITP). The university’s Computer Science research has also been rated 90% world-leading in the UK’s REF 2021 assessment.

### Research Opportunities
Students enrolled in this programme have opportunities to work on cutting-edge research topics in areas like machine learning, data ethics, big data, and AI. The Advanced Research route allows students to engage in extended research suitable for publication or PhD-level preparation.

### Tools and Technologies Covered
Throughout the course, students will use a variety of modern tools and frameworks, including:
- Python (NumPy, pandas, scikit-learn)
- R
- MATLAB
- SQL
- TensorFlow and PyTorch

### Learning Outcomes
Upon successful completion of the MSc Data Science and Analytics programme, students will be able to:
- Evaluate complex data sets using statistical and machine learning techniques.
- Design data processing pipelines for real-world analytics challenges.
- Communicate technical findings to non-technical stakeholders.

### Student Testimonials
“After completing this MSc, I joined Deloitte as a Data Analyst working on AI audit tools.”
“Placement at Sky gave real‑world hands‑on experience in large‑scale data engineering.”

### Why Choose This Course?
This programme stands out because of its strong practical focus, use of modern data science tools, and multidisciplinary teaching delivered by top-tier researchers. The option to choose between a research-focused or industry-focused route provides flexibility based on your long-term career goals.

### Official Links
To view more detailed and up-to-date information about this programme, visit the official course page:
- Official Course Page: https://www.herts.ac.uk/courses/postgraduate-masters/msc-data-science-and-analytics

If you are ready to begin your application, you can do so here:
- Click here to apply: https://www.herts.ac.uk/study/postgraduate/how-to-apply