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3 Years On Campus Bachelors Program
London School of Economics and Political ScienceThe BSc Mathematics with Data Science at the London School of Economics & Political Science (LSE) seamlessly integrates rigorous mathematical theory with cutting-edge data science techniques. This program is ideal for students aiming to apply mathematical principles to real-world challenges in fields like economics, finance, and technology.
Curriculum Structure:
Year 1: Students begin with foundational courses such as MA103 Introduction to Abstract Mathematics, ST101A Programming for Data Science, and ST202 Probability, Distribution Theory and Inference. These modules establish a solid base in mathematics and programming essential for data analysis. Additionally, students engage in LSE100, a half-unit course that addresses pressing global issues like climate change or AI governance.
Year 2: The second year delves deeper into specialized topics, including MA209 Differential Equations, MA210 Discrete Mathematics, and ST207 Databases. Students also explore advanced statistical methods through ST206 Probability and Distribution Theory, preparing them for complex data analysis tasks.
Year 3: In the final year, students have the opportunity to choose from advanced courses such as MA316 Graph Theory, ST310 Machine Learning, and ST311 Artificial Intelligence. These electives allow students to tailor their studies to specific interests, culminating in a comprehensive dissertation project.
Focus Areas: Mathematical Modelling, Machine Learning, Artificial Intelligence, Data Analysis, Statistical Inference
Learning Outcomes: Proficiency in mathematical reasoning, advanced data analysis techniques, programming skills, and the ability to apply mathematical models to real-world problems.
Professional Alignment: The program is designed to meet the accreditation standards for quantitative disciplines, preparing graduates for roles in data science, finance, and technology sectors.
Reputation: LSE consistently ranks among the top universities globally, renowned for its strong employability outcomes and influential alumni network.
The BSc Mathematics with Data Science at the London School of Economics & Political Science (LSE) offers students a dynamic mix of theoretical mathematics and practical data science skills. This program focuses on experiential learning, ensuring students not only understand complex mathematical ideas but also know how to apply them in real-world settings. Through hands-on opportunities, students can connect classroom knowledge with practical industry experience.
Experiential learning in this program includes:
Field Trips to Industry Leaders: Students get the chance to visit leading data science organizations, such as Google, The Bank of England, and The Cabinet Office, giving them a real insider’s perspective on how data science is applied in different sectors.
Digital Skills Lab: Situated within the LSE Library, the Digital Skills Lab provides training in essential software tools, helping students become proficient in the programs and technologies needed for data analysis and programming.
Group Study Rooms and IT Facilities: The LSE Library offers over 2,300 study spaces, including group rooms, alongside extensive IT facilities with more than 300 PCs, laptop points, and wireless Internet access, supporting collaborative work and research.
Moodle Platform: LSE’s online learning platform, Moodle, allows students to easily access course materials, submit assignments, and utilize a wide range of resources, enhancing their learning experience.
LSE Careers Networking Events: Regular coffee mornings and networking sessions hosted by LSE Careers bring employers from diverse sectors, including data science and technology, directly to students, offering valuable insights into industry trends and career paths.
These experiential learning opportunities are designed to give students practical skills, industry exposure, and confidence, preparing them to thrive in the fast-growing field of data science.
Graduates of the BSc Mathematics with Data Science from the London School of Economics and Political Science (LSE) leave with a strong and versatile skill set. By combining rigorous training in mathematics, statistics, and data science, the program equips students to take on challenging and rewarding roles across sectors such as finance, technology, and consulting.
Typical Career Paths:
Data Scientist: Use statistical models and machine learning to uncover insights from complex datasets and drive informed decision-making.
Quantitative Analyst: Apply mathematical techniques to financial markets, helping organizations develop effective investment strategies.
Machine Learning Engineer: Design and implement algorithms that allow machines to learn from data and make intelligent predictions.
Consultant: Advise businesses on leveraging data to improve performance and inform strategic decisions.
University Support & Industry Connections:
Career Services: LSE’s Careers division provides personalized guidance, workshops, and lectures to help students confidently navigate the job market.
Industry Partnerships: Collaborations with leading institutions and research networks give students exposure to cutting-edge developments in data science and artificial intelligence, along with valuable networking opportunities.
Accreditation: The program’s strong academic foundation ensures that graduates earn a globally recognized qualification, enhancing career prospects.
Further Academic Progression:
MSc Data Science: Expand your undergraduate knowledge by exploring advanced statistical methods, machine learning, and data mining, preparing for senior roles in data science.
MSc in Financial Mathematics: For those drawn to finance, this program offers in-depth training in mathematical approaches applied to financial markets.
PhD Programs: Pursue advanced research in areas like machine learning, AI, or applied mathematics, opening doors to academic positions or high-level industry roles.
Choosing the BSc Mathematics with Data Science at LSE not only gives you a solid grounding in quantitative analysis but also opens up a wide range of career paths and further academic opportunities, making it an ideal stepping stone for ambitious students.
A*AA, with an A* in Mathematics; A-level courses such as Physics or Chemistry provide excellent preparation, although these subjects are not mandatory.IB: 39 points overall, including 766 in higher level subjects, with 7 in "Mathematics: analysis and approaches"IELTS Academic: 7.0 overall; 7.0 in each component; achieved in a single exam; valid within 2 years before programme start (1 September)TOEFL iBT (including Home and Paper Editions) 100 overall; minimum scores: Writing 27; Reading 25; Listening 24; Speaking 24; achieved in a single exam sitting within 2 years prior to programme start (1 September).For Indian Applicants: An overall average of 95 per cent or above, with 3 subjects at 95 per cent or above and 2 subjects at 90 per cent or aboveA mark of 95 per cent in Mathematics for programmes requiring an 'A*' in A-level Mathematics.For US Applicants: 5 APs at grade 5, taken over a maximum of 3 years and a minimum High School Diploma GPA 3.7 Or a minimum High School Diploma GPA of 3.7, and an ACT score of 32+ or an SAT score of 1450+ (with AP Calculus BC at grade 5).For GCSEs, you’ll need a strong pre-16 academic profile such as several GCSE grades of A (or 7) and A* (or 8-9).Data AnalystData ScientistBusiness AnalystQuantitative AnalystMachine Learning EngineerStatisticianActuarial AnalystRisk AnalystOperations Research AnalystAI SpecialistFinancial AnalystResearch Scientist
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