| Program start date | Application deadline |
| 2024-09-26 | - |
| 2025-09-26 | - |
Program Overview
The BSc (Hons) Data Science program at the University of Hertfordshire equips students with the skills and knowledge to thrive in the data-driven world. It combines fundamental mathematical and statistical expertise with cutting-edge Data Science concepts, preparing graduates for a diverse range of lucrative careers. The program emphasizes practical learning through laboratory sessions, project work, and industry-relevant simulations, instilling confidence and independence in students' technical capabilities. Graduates possess a rigorous understanding of mathematical and statistical principles, employ advanced data analysis and processing techniques, and contribute effectively in collaborative research environments.
Program Outline
Degree Overview:
Overview:
The BSc (Hons) Data Science program at the University of Hertfordshire equips students with the multifaceted skills and knowledge required to thrive in the data-driven world. It combines fundamental mathematical and statistical expertise with cutting-edge Data Science concepts, preparing graduates for a diverse range of lucrative careers. The program has a strong emphasis on practical learning, with laboratory sessions, project work, and industry-relevant simulations designed to instill confidence and independence in students in their technical capabilities.
Objectives:
The BSc (Hons) Data Science program cultivates graduates who:
- Possess a rigorous understanding of mathematical and statistical principles.
- Employ advanced data analysis and processing techniques.
- Develop innovative solutions to contemporary societal challenges.
- Display expertise in handling large datasets and high-performance computing.
- Contribute effectively in collaborative research environments.
- Communicate data-driven discoveries with clarity and expertise.
Unique program features:
- Neuromorphic computing and exoplanet detection: The program incorporates insights from the University's world-leading research in these areas, providing students with exposure to cutting-edge advancements.
- Industry-relevant practical skills: Hands-on learning through data science laboratories and projects ensures students gain critical practical skills alongside theoretical knowledge.
- Research-oriented seminars and colloquia: Students have the opportunity to attend seminars and learn from leading researchers in diverse fields, fostering intellectual curiosity and a vibrant learning environment.
- Success and Skills Support Unit: This dedicated unit helps students develop their employability and academic skills, providing vital support for their career aspirations.
- Industry mentors: Students benefit from mentorship from industry professionals who offer guidance, career progression opportunities, and pastoral support.
Outline:
Program Level:
Undergraduate
Degree Title:
BSc (Hons) Data Science
Study Mode:
Full-time, Part-time, Sandwich (with placement)
Study Duration:
- Full-time: 3 years
- Part-time: 6 years
- Sandwich: 4 years
Semester Structure:
- Level 4: 2 semesters
- Level 5: 2 semesters
- Level 6: 2 semesters
Total Credits:
360
Course Delivery:
- Lectures
- Laboratories (Data Science Laboratory 1 & 2)
- Seminar participation
- Guided and independent study
- Project work
- Placement opportunities for sandwich students
Course Structure:
The program is structured into three levels, each with specific modules designed to progressively build upon acquired knowledge and skills.
Level 4:
Module:
|
- --|---|---|--- Mathematical Methods | 15 | Compulsory | Introduces fundamental mathematical concepts and develops analytical and problem-solving skills. Probability and Statistics | 15 | Compulsory | Provides comprehensive grounding in probability theory and statistical analysis techniques. Linear Algebra | 15 | Compulsory | Explores the intricacies of linear algebra with applications in various disciplines. Computational Modelling | 15 | Compulsory | Introduces programming languages and computational methods for scientific and mathematical modeling. Principles of Data Science | 15 | Compulsory | Presents fundamental concepts of data science and its practical applications. IT Literacy and Core Skills | 15 | Compulsory | Equips students with essential IT skills and mastery of LaTeX document preparation. Data Science Laboratory 1 | 15 | Compulsory | Focused on practical data science training, including coding, data engineering, and computational problem-solving approaches. Data Science Small Group Tutorial 1 | 0 | Compulsory | Provides support for problem-solving skill development and addresses academic or personal challenges encountered during the first year.
Level 5:
Module:
|
- --|---|---|--- Programming | 15 | Compulsory | Delves deeper into programming practices including control structures, debugging, and program documentation. Game Theory | 15 | Compulsory | Introduces strategic modeling and game theory concepts for optimizing decision-making in various scenarios. Statistical Modelling | 15 | Compulsory | Explores advanced statistical methods involving analysis of variance and regression analysis Career Planning and Development | 0 | Compulsory | Focuses on career development skills and understanding the role of graduates in the work environment. Big Data and High-Performance Computing | 15 | Compulsory | Equips students with knowledge on storing, analyzing, and mining large datasets using high-performance computing resources. Blockchains and Cryptocurrencies | 15 | Compulsory | Examines blockchain technology, its applications, cryptocurrency fundamentals, and practical implementations with Python. Data Science Laboratory 2 | 15 | Compulsory | Focuses on practical data analysis tools and techniques for data preparation, processing, and exploration. Introduction to Machine Learning and Neural Networks | 15 | Compulsory | Introduces the fundamentals of machine learning and artificial intelligence, implementing techniques with appropriate programming languages. Data Science Small Group Tutorial 2 | 0 | Compulsory | Continues academic support and provides guidance for career development planning.
Level 6:
Module:
|
- --|---|---|--- Linear Modelling | 15 | Compulsory | Explores powerful linear modeling techniques for analyzing data with multiple outcome variables. Multivariate Statistics | 15 | Compulsory | Introduces sophisticated statistical methods for analyzing data with multiple outcome variables. Data Science Project | 30 | Compulsory | Major research project requiring students to independently apply their developed skills and knowledge while exploring a specific topic in data science. Next Generation Data Science | 15 | Compulsory | Provides insights into cutting-edge advancements in data science, including hardware and software innovations, and their potential impact on societal challenges. Computer Vision and Natural Language Processing | 30 | Compulsory | Explores image recognition, object classification, speech segmentation, and other fundamental techniques in computer vision and natural language processing. Advanced Machine Learning and Neural Networks | 15 | Compulsory | Builds upon Level 5 knowledge to explore advanced concepts in machine learning and artificial intelligence, including deep neural networks and their applications.
Assessment:
The program utilizes diverse assessment methods catering to various learning styles and ensuring comprehensive evaluation of student acquisition of knowledge and application of skills.
Assessment methods include:
- Exams: Assessing theoretical knowledge and understanding of key concepts.
- Coursework: Practical assignments, reports, and essays to evaluate problem-solving abilities and practical application of acquired knowledge.
- Presentations: Assessing communication skills and ability to present data-driven insights effectively.
- Laboratory work: Evaluates students' practical skills and data analysis abilities in a hands-on environment.
- Data Science Project: A major project assessed through a combination of reports, presentations, and demonstrations of independent research and execution.
Teaching:
Teaching methods:
- Lectures: Provide students with a strong foundation in theoretical concepts and methodologies.
- Laboratory sessions: Hands-on training in data Science techniques and tools through practical exercises focusing on data manipulation, analysis, and interpretation.
- Seminars: Guest lectures from researchers and industry professionals provide insights into current happenings and future trends in the field.
- Group work and collaborative projects: Encourage teamwork, communication, and problem-solving in a collaborative environment.
Faculty:
Academic staff within the School of Computer Science, Engineering, Physics, and Physical Sciences possess extensive experience and expertise in data science. They are actively involved in relevant research, ensuring students receive up-to-date knowledge and insights.
Unique Teaching Approach:
- Emphasis on practical learning: The program prioritizes hands-on laboratory work and projects to equip students with essential data science skills for real-world application.
- Small group tutorials: Personalized support and dedicated time for addressing individual challenges and fostering in-depth understanding.
- Industry-relevant content: The program incorporates current industry practices and emerging trends, ensuring graduates are prepared for the current job market.
- Research-active environment: Students have access to world-leading research and opportunities to participate in cutting-edge projects.
Careers:
Career paths:
Graduates of the BSc (Hons) Data Science program acquire skills and knowledge enabling them to pursue diverse career paths in various sectors, including:
- Data Scientist
- Data Analyst
- Data Engineer
- Machine Learning Engineer
- Artificial Intelligence Specialist
- Operations Research Analyst
- Statistical Modeler
- Financial Analyst
- Marketing Analyst
- Business Intelligence Analyst
- Data-driven Journalist
- Healthcare Data Analyst
Career opportunities:
The program opens doors to opportunities in various industries, including finance, banking, healthcare, retail, technology, government, research, and education.
Graduate employment:
The University of Hertfordshire has a dedicated careers service assisting graduates with job search and career development. Moreover, the program's strong industry connections and emphasis on practical skills enhance graduates' employability in the competitive data science job market.
Other:
- Study abroad options: Students can enhance their global perspective and intercultural skills through semester-long study abroad programs at partner institutions worldwide.
- Sandwich placements: Students can gain valuable industry experience through integrated placements with leading companies.
- Modern facilities: Students have access to modern computer labs, high-performance computing facilities, and industry-standard software for optimal learning and research.
UK Students Full time £9250 for the 2024/2025 academic year Part time £1155 per 15 credits for the 2024/2025 academic year EU Students Full time £15500 for the 2024/2025 academic year Part time £1940 per 15 credits for the 2024/2025 academic year International Students Full time £15500 for the 2024/2025 academic year Part time £1940 per 15 credits for the 2024/2025 academic year
Hertfordshire International College
Overview:
Hertfordshire International College (HIC) is a pathway college dedicated to helping students achieve their career goals. It offers a range of undergraduate and postgraduate pathway programs designed to prepare students for prestigious degrees at the University of Hertfordshire. HIC emphasizes a supportive and engaging student experience.
Services Offered:
HIC offers a variety of services to support students, including:
Pre-Sessional English:
A course to improve English language skills for international students.Undergraduate Pathway Programs:
Foundation and first-year level programs in various disciplines.Postgraduate Pathway Programs:
Pre-Master's programs to prepare students for postgraduate studies.Student Life and Campus Experience:
HIC provides a vibrant and diverse campus environment with modern facilities. Students can expect:
Campus Location:
Just 25 minutes from London.Modern Facilities:
Continuously invested in and updated.Supportive Environment:
A welcoming and supportive atmosphere for international students.Student Life Activities:
Opportunities to enhance the international student experience.Key Reasons to Study There:
University of Hertfordshire Affiliation:
Provides access to a reputable university with strong research capabilities.Research Excellence:
Ranked in the top 25% of UK universities for research impact.World-Leading Research:
78% of research considered 'world-leading'.Enterprise Zone Status:
One of only 20 universities with this designation.Top Rankings:
Ranked 1st in the UK for Paramedic Science.Academic Programs:
HIC offers a wide range of academic programs across various disciplines, including:
Undergraduate:
Accounting and Finance, Animation, Film, Games and Creative Media, Architecture, Art, Design and Fashion, Biological Sciences, Psychology and Sport, Business and Economics, Computer Science, Cyber Security and Data Science, Education and Teaching, Engineering, AI and Robotics, English and Linguistics, Geography and Environment, Health, Nursing and Midwifery, Law and Criminology, Media, Journalism and Politics, Music Composition, Technology and Production, Physics, Astrophysics and Mathematics, Tourism and Event Management.Postgraduate:
Animation, Film and Creative Media, Art and Design, Business and Management, Education and Teaching, Finance and Investment Banking, Master of Business Administration, Music Composition, Technology and Production, Tourism and Event Management.Entry Requirements:
EU Home Students
Level 4:
- GCE A Level: BBB including a minimum of grade B in mathematics.
- BTEC (QCF): DDM in a relevant subject area, including a minimum of Merit in mathematics.
- Access to HE Diploma: Pass with 45 credits, including 15 credits in mathematics at a minimum of Merit.
- International Baccalaureate: 120–128 points including a minimum of grade 4 at HL in mathematics.
Additional Requirements:
- Grade 4 GCSE in English Language and Mathematics.
- Successful completion of Pre-sessional English course if required.
International Overseas Students (outside the EU)
Level 4:
- GCE A Level: BBB including a minimum of grade B in mathematics.
- BTEC (QCF): DDM in a relevant subject area, including a minimum of Merit in mathematics.
- Access to HE Diploma: Pass with 45 credits, including 15 credits in mathematics at a minimum of Merit.
- International Baccalaureate: 120–128 points including a minimum of grade 4 at HL in mathematics.
Additional Requirements:
- IELTS Academic: Overall score of 6.0 with no less than 5.5 in any band.
- Successful completion of Pre-sessional English course if required.
Language Proficiency Requirements:
- Applicants whose first language is not English must demonstrate proficiency in English by achieving the required IELTS score of 6.0 with no less than 5.5 in any band.
- Successful completion of a Pre-sessional English course may be required for applicants who do not meet the minimum English language requirements. Specific requirements may vary depending on your chosen pathway or if you are applying for advanced entry.
