Program Overview

Introduction to Mathematics with Data Science and Artificial Intelligence BSc

The Mathematics with Data Science and Artificial Intelligence BSc is an interdisciplinary program that combines traditional mathematical techniques with state-of-the-art applications in the field of data science and artificial intelligence (AI). This degree will equip students with a sound background in the techniques of mathematics and statistics, training in data science tools, computational and programming skills, as well as an understanding of data science practice.

Course Description

The program is designed to provide students with a mathematical foundation and the interdisciplinary skills needed for a successful career in data science and AI. Students will gain expertise in handling large sets of data and drawing knowledge, patterns, and trends from these data sets. The degree will cover machine learning and AI, statistical and mathematical modelling, and teach a range of programming languages.

Key Features

• Interdisciplinary program combining mathematics, data science, and AI
• Sound background in mathematical techniques and statistics
• Training in data science tools and computational skills
• Understanding of data science practice and machine learning
• Range of programming languages, including R, Python, and Matlab

Entry Requirements

To be eligible for the program, students must meet the following entry requirements:

• A/AS-levels: ABB including Maths
• Two AS-levels considered in place of one A-level
• EPQ with A-levels: BBB + EPQ at grade B
• A-level subjects to include Maths
• Access to HE Diploma: Pass Diploma with a minimum of 45 credits at level 3, 30 of which must be at Distinction
• Plus A-level Maths at grade A-B
• International Baccalaureate: Pass Diploma with 30 points including grade 5 in HL Maths
• BTEC Nationals: Pass Extended Diploma with DDM, plus grade B in A-level Maths

Contextual Offers

The University of Leicester is committed to providing equitable opportunities for all applicants from all backgrounds. Contextual offers are made to support students who may be impacted by the area they live in, their personal circumstances, or who have completed one of the university's progression programmes. These offers are usually one or two grades lower than the standard entry requirements.

Fees and Funding

The tuition fees for the program are as follows:

• UK Students: ｣9,535 in the first year, with potential increases in subsequent years
• International Students: ｣25,100 per year
• Year in Industry: ｣1,905 for UK students, ｣3,765 for international students (15% of the full-time tuition fee)

Additional Costs

Students will need to purchase a Casio FX83GT calculator, approximately ｣6, which is not included in the tuition fee.

Careers and Employability

The program will prepare students for a career as a data professional, with career opportunities such as:

• Machine Learning Engineer
• Data Engineer
• Software Architect
• Data Science Consultant
• Data Scientist
• Data Architect
• Database Administrator

Employability Statistics

• 94% of graduates in skilled work or further study 15 months after graduation
• Joint 2nd for employability in the UK
• UK Top 30 university, 3rd in the UK for Mathematics

Facilities

Students will have access to:

• The Percy Gee Computer Laboratory
• The David Wilson Library Computer Laboratory
• A Student Study and Social Space in the Ken Edwards Building

Teaching and Learning

The program will involve lectures, group meetings, and problem classes. A typical week for a first or second-year student might consist of nine or ten hours of lectures, around four hours of small group working, and about three hours of problem classes or computer classes.

Assessment

Assessment will be via coursework, computational exercises, projects, and written exams.

Independent Learning

Students will be expected to continue learning independently through self-study, including reading journal articles and books, working on individual and group projects, and preparing for exams.

Academic Support

The Centre for Academic Achievement provides help with study and exam skills, academic writing, presentations, and dissertations. The AccessAbility Centre offers support and practical help for students with dyslexia or other specific learning difficulties.

Teaching Staff

Students will be taught by an experienced teaching team whose expertise and knowledge are closely matched to the content of the modules on the course. PhD research students who have undertaken teacher training may also contribute to the teaching of seminars under the supervision of the module leader.