Online Career Accelerator

Data Analytics

Developed in collaboration with leading technology companies, this programme prepares you to accelerate your career as a Data Analyst in the digital economy.

Download a brochureExternal LinkBook a callExternal Link

Key details

  • Programme type
    Online Career Accelerator
  • Location
  • Start date
    14 Oct 2024  -  Open
  • Duration
    6 months
  • Commitment
    15 - 20 hours per week
  • Department
    Department of Statistics, Department of Methodology


As data volumes continue to grow exponentially, the ability to transform this information into actionable business insights is a key capability in the ‘Age of Analytics’. Demand for data analytics skills is rocketing as a result, offering career starters and established professionals alike the opportunity to align to a high-growth path valued by organisations across industries.

Designed by LSE faculty from the Departments of Methodology and Statistics, the LSE Data Analytics Career Accelerator aims to accelerate your career through both its subject focus and education model. Following a project-based approach to learning, you’ll develop fundamental data analytics competencies with immediate and long-term relevance in the digital economy. You’ll be introduced to the core concepts of data analysis, learn to use visualisations to communicate insights through storytelling, and apply technical knowledge of programming to business use-cases. With input from leading technology companies, you’ll engage directly with the tools used in industry and practise their use in project-based exercises.

As you learn from LSE faculty, you’ll have access to a network of Success Managers, Career Coaches and Facilitators to support you with programme progress, career planning and subject-related challenges. This powerful support team ensures you’re able to reach your potential in the programme, and in the career it prepares you for. 

Do you want to find out how data skills can expand your career?

Read this article, based on a webinar featuring Associate Professorial Lecturer from LSE's Department of Statistics, Dr. James Abdey, and Danilo Sato, Head of Data and AI Services UK at Thoughtworks.


  • Align data collection and management to business objectives as you conduct best practice data-wrangling activities
  • Empower businesses to make informed decisions by using engaging visualisations to tell a compelling story with data
  • Critically analyse and address the ethical and social issues of data analysis
  • Collaborate remotely with a diverse peer group and develop your ability to create business value through a multi-disciplinary approach to problem solving
  • Work with Success Managers and Career Coaches to demonstrate self-reflection that improves career outcomes
  • Develop a project-based portfolio as proof of your technical abilities and their relevance to employers
  • Earn an LSE certificate as globally-relevant recognition of your new knowledge and competencies

Programme content

This online career accelerator is delivered over 6 months (excluding onboarding) with a time commitment of approximately 15 - 20 hours per week.

Who attends?

  • Career starters looking to build a data analytics skill set with long-term relevance in the digital economy
  • Professionals realigning their career path to enter a high-growth industry at the core of business strategy and operations
  • Current or aspiring Data Analysts looking to fast-track their data analytics careers
  • Established professionals aiming to retain their relevance by developing in-demand digital skills underpinned by the value of a world-leading university

Why LSE?

LSE Online builds on our 125 year tradition of exploring the interconnected, multidisciplinary nature of our world that shape society and business globally. Since our inception in 1895, LSE has been a pioneer in providing courses for professional development. Our founding commitment is to understand the causes of things for the betterment of society. Never has this been a more important goal than in these times of unparalleled change. We provide you with the insights and skills to think critically and independently. To make the connections, see the greater picture. To shape the future by understanding today. Whatever stage you are in your life and career. Wherever you are in the world.


This career accelerator is designed by LSE faculty in collaboration with industry experts and leading technology companies to align programme outcomes with industry demand.

James Abdey

Dr James Abdey

Associate Professorial Lecturer of Statistics

Christine Yuen

Dr Christine Yuen

Assistant Professorial Lecturer in Statistics

Milena Tsvetkova

Dr Milena Tsvetkova

Assistant Professor of Computational Social Science

Blake Miller

Dr Blake Miller

Assistant Professor of Computational Social Science

Milt Mavrakakis

Dr Milt Mavrakakis

Guest Lecturer in Statistics

Department overview

The Department of Statistics is home to internationally respected experts in statistics and data science. Maintaining and advancing our leading reputation for teaching and research is our top priority. The department offers a vibrant research environment with specialisms in four main areas: data science, probability in finance and insurance, social statistics, and time series and statistical learning.

The Department of Methodology is an internationally recognised centre of excellence in research and teaching in the area of social science research methodology. The disciplinary backgrounds of the staff include political science, statistics, sociology, social psychology, anthropology and criminology.

Fees and entry requirements

Tuition fees: £7,695 if you pay upfront.

Flexible payment options available. LSE alumni automatically qualify for a preferential rate of 15% off the programme fee.

Upon successful completion of this career accelerator, you’ll leave with a practical portfolio to demonstrate your technical expertise, and earn an LSE certificate as recognition of your critical knowledge and skills.

Entry requirements

Applicants should be able to demonstrate foundational technical skills, either through relevant educational or employment experience, or by passing a technical test. English language proficiency is a prerequisite. Those who meet the initial requirements must then complete an admissions interview to further demonstrate competency and aptitude, as well as attitudinal fit appropriate to the programme’s intensive nature.