Full-Time or Part-Time Programme
Data Science Bootcamp London
Launch a new career in Data Science and Artificial Intelligence with this intensive Data Science bootcamp in London.
View the Programme Package to access:
- Tuition details
- Scholarships and financing options
- Application process
Become a
Data Scientist
Graduate Success
Thousands
of graduates from our bootcamp programs globally
cutting-edge data science curriculum
connect with top employers
world-class career services
Alumni Stories
Data Science
Bowen
Analytics Engineer
Aviel
Senior Data Analyst
BrainStation Students Work at Amazing Companies
BrainStation gave me the belief that a career change was achievable rather than just a pipe dream.
Edward Jackson
Data Scientist at Office for National Statistics
Read Full testimonial
Our Network of Industry Partners and Experts
BrainStation is proud to work with some of the world's leading digital brands and professionals to power our events, courses, and bootcamp experiences.
The Data Science Bootcamp Experience
BrainStation is more than a Data Science bootcamp: it's a career transformation experience. Develop essential data science skills and gain hands-on, industry experience through unique real-world projects. Learn in our new, state-of-the-art campus in London's bustling Shoreditch tech district, where you'll work alongside industry professionals on real business problems and collaborate with Designers, Web Developers, Software Engineers, and Digital Marketers to deliver real-world solutions. See why thousands of graduates have launched their new careers with BrainStation through this Data Science bootcamp.
Hands-On Data Science Industry Experience
Get practical, hands-on data science experience, applying what you've learned to a real business case presented by a leading digital business like Microsoft, Mastercard, and Google. In these dynamic data science industry projects, you'll work alongside industry practitioners while cross-collaborating with BrainStation students from other bootcamps to develop a compelling digital solution. This is an essential experience, applying your technical skills to a real-world business problem and working as part of a diverse digital team, just like you will in your new career as a Data Scientist.
INDUSTRY PARTNER
The Challenge
How might we increase the security of digital transactions through innovative digital solutions?
Working in cross-functional teams alongside practitioners from Mastercard, BrainStation students designed and built human-centered solutions to this challenge, and presented them to Mastercard leadership.
INDUSTRY PARTNER
The Challenge
What digital solutions can we use to support the future success of eCommerce in the apparel and sporting goods industry?
BrainStation students were challenged to work with practitioners from adidas to design and build an innovative solution to this challenge. At the end, they had the opportunity to present their solution to adidas.
INDUSTRY PARTNER
The Challenge
How might we increase access to health care services through the use of education and digital solutions?
Working in cross-functional teams alongside practitioners from Google, BrainStation students collaborated to design and build innovative solutions to this challenge. Once complete, students then had the opportunity to present their solutions back to Google.
INDUSTRY PARTNER
The Challenge
What data-driven, digital experiences can we deliver to help customers to save money and live better?
Working in cross-functional teams alongside practitioners from Walmart, BrainStation students designed and built human-centered solutions to this challenge, and presented them to the Walmart team.
INDUSTRY PARTNER
The Challenge
As the restaurant industry is experiencing significant disruption, what digital solutions can we create to support successful food delivery?
Working alongside practitioners from SkipTheDishes, BrainStation students designed and built a solution to this challenge facing the restaurant industry. They then presented their solutions to SkipTheDishes leadership.
Learn From Guest Data Science Experts Throughout the Programme
BrainStation students get access to exclusive guest lectures and panel discussion events led by some of the world's top Data Scientists, leading subject matter experts, and data industry professionals.
Location
Learn in the Centre of London
Based in the tech district of Shoreditch, BrainStation is at the heart of London's digital scene, surrounded by the most cutting-edge companies in the city. In addition to courses, BrainStation London offers training sessions, industry events, expert panel discussions, and more.
BrainStation London55-57 Rivington Street, London, EC2A 3QA, UK
Start Learning Full-Time or Part-Time
Full-time classes are held all day, Monday to Friday.
Full-Time Schedule
In-Person or Online
Classes on Monday to Friday
Daily Schedule
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8:45 AM
Pre-Class prep
Grab a coffee and pastry to kick-start your day, and arrive at the campus to get settled in.
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9:00 AM
Morning kickoff
Jump into a morning kickoff, focused on reviewing critical content, introducing a new topic, or diving into a hands-on activity to prepare you for the data science work ahead.
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9:30 AM
Lecture
Explore new topics through interactive lectures filled with code demos, real-world examples, and bite-sized activities to help you learn and apply new concepts. Lectures often involve the use of Jupyter Notebooks, a Python development tool that provides an interactive, self-contained coding environment to help you experiment, test new code, and learn new skills quickly.
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12:00 PM
Lunch
Recharge over lunch with your peers at the campus, or visit some top-notch eateries located moments away.
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1:00 PM
Lecture and lab challenge
Close off the topics from the morning lecture, or extend your learning by exploring new data science concepts in an afternoon lecture. Develop your skills by practising what you've just learned through a structured lab challenge – both as an individual and through small groups, or write code live, alongside a demonstration from your Educator.
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3:00 PM
Project work and one-on-one coaching sessions
Incrementally apply what you've learned through structured unit projects, and work with a member of the education team for personalised support and development, preparing you for your new career.
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5:00 PM
End of day
Close off a dynamic learning day and head home to recharge.
Part-Time Schedule
Online
Classes on two weekday evenings and Saturday
Weekly Schedule
Two Weekday Evenings
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Lesson
Explore new topics through interactive lectures filled with demos, real-world examples, and bite-sized activities to help you learn and apply new concepts. You'll also take part in structured lab challenges designed to solidify your learnings through solving engaging problems.
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Guided work session
Review your learnings from the day, connect with the Education Team to resolve questions, and spend time working towards curated unit projects that support your portfolio.
Saturday
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Guided work session and morning kickoff
Jump into a morning kickoff, focused on reviewing critical content, introducing a new topic, or diving into a hands-on activity. Work on unit projects, and get guided support to achieve learning objectives.
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Morning lesson
Continue your learning with an interactive lecture and lab challenge, building on what you've covered earlier in the week.
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Lunch
Take a break and recharge over lunch. Connect with your peers online or take some time to step away and take care of items that come up during the day.
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Afternoon lesson
Close off the topics from the morning lecture, or further your learning with an afternoon lecture. Depending on the topic, you'll also dive into a lab challenge or guided exercise to help you understand and connect new concepts.
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Collaboration, coaching, and work sessions
Close off a dynamic week by spending time to absorb and apply what you've learned. This structured time might be spent between working on unit projects, collaborating with peers to solve challenges, and reviewing questions with a member of the Education Team, all to build your mastery of new subjects.
Unit 1
Fundamentals: Data Analysis & Visualisation
Begin your data science journey by developing critical data skills in data analysis, business intelligence, and visualisation. Build a strong foundation and prepare yourself for more advanced work ahead by learning about data types, how to work with them, and more. In this unit, you'll also explore the world of databases, and how to work with relational database management software (MySQL) to model, structure, and manipulate data for analysis. You will also begin learning about programming through SQL, enabling you to write powerful queries to perform data operations. Finally, you'll use Tableau, an industry-standard tool, to craft dynamic visualisations and dashboards that effectively communicate insights to others.
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- Key Skills:
- SQL
- Databases
- Data Modelling & Schema
- Data Analysis
- Data Visualisation
- Dashboards
Learn Fundamental Data Science Concepts
Real-world data analytics often involves working with larger and more complex data sets. Build an understanding of data types, relational databases, schema, data mining, and data processing, and use industry tools like MySQL to begin the data analytics process. By learning these key concepts, you'll be better prepared to tackle the advanced work ahead.
Learn SQL to Manipulate Data and Perform Data Analysis
Structured Query Language (SQL) is a powerful programming language and one of the essential programming skills needed for a career in data. Learn how to write advanced expressions with SQL to process data, surface key data points, highlight patterns, and augment your search capabilities within large data sets and prepare for business intelligence.
Communicate Data Insights With Powerful Data Visualisations
Learn critical concepts to design impactful visualisations that communicate your data analytics insights – when to use different chart types, visualisation design, dashboarding, along with best practises for accessibility, colour use, and more. Use Tableau – an industry-leading business intelligence and visualisation tool – to augment your analysis and distil the most important insights into clear visualisations.
Unit 2
Analysis for Data Science
Data science work relies on programming with languages such as Python and R. In this unit, you'll build core programming skills and leverage data science tools to perform complex data science work. You'll learn how to gather data from the web, complete data wrangling, and use code to perform analysis, build visualisations, and present insights. This unit is filled with essential data science knowledge and is your crash course for core data science skills and capabilities, orienting you for more advanced work ahead.
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- Key Skills:
- Python
- Object-Oriented Programming (OOP)
- Data Cleaning
- Exploratory Data Analysis (EDA)
- Statistical Analysis
- Hypothesis Testing
- Predictive Models
- APIs & Web Scraping
- Command Line Scripting
- Python Data Visualisation
- Code Version Control
Master Programming and Python for Data Science
Python is an essential skill and one of the most important tools for data science, providing unique power and flexibility to handle large volumes of data. Through this programme, you'll learn fundamental programming concepts that will also help you learn other languages in the future, and you'll use Python to perform data cleaning, analysis, visualisation, and more.
Learn Essential Statistical Analysis Concepts
In this unit, you'll explore important statistics concepts including central tendency, dispersion, covariance, and more, learning how to incorporate them into your analysis. You'll also practise how Data Scientists perform hypothesis testing to uncover insights, and you'll build predictive models using linear and logistic regression analysis.
Perform Advanced Data Work Using Industry Tools
Data Scientists use an ecosystem of tools to help them perform more advanced work quickly and efficiently. You'll learn how to work with Python packages and libraries to extend Python's capabilities, and use command line and git to manage your code. You'll also explore new tools commonly used in data science – the programming language R, and Tidyverse (a collection of packages), among others.
Unit 3
Artificial Intelligence & Machine Learning Techniques
Machine learning is an integral part of data science and has become commonplace today, powering many of the digital services and technologies used by businesses and consumers. In this unit, you'll dive deep into machine learning fundamentals, and explore a variety of techniques and algorithms used as part of this subset of data science. You'll also explore a variety of industry tools used to build machine learning models and gain hands-on practise learning and applying machine learning concepts.
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- Key Skills:
- Generative AI
- Prompt Engineering
- Machine Learning
- Supervised Learning
- Unsupervised Learning
- Feature Engineering
- Text Analysis (NLP) & Image Processing
- Model Evaluation
- Exploratory Data Analysis (EDA)
Learn Essential Machine Learning Concepts and Cutting-Edge Industry Tools
Explore machine learning and how it can be applied in practical, real-world scenarios. You'll also use Python, along with a number of packages and other tools to understand how machine learning models function, and practise applying supervised and unsupervised machine learning techniques.
Apply Machine Learning Techniques for Data Analysis & Predictive Modelling
Learn to perform exploratory data analysis and feature engineering to explore trends in diverse data sets. You'll perform predictive modelling and work with unstructured data like natural language text and images in machine learning models. Learn to evaluate models to determine the accuracy of your results.
Explore Generative AI & Prompt Engineering
Learn about Large Language Models (LLMs) including ChatGPT, and the AI technologies behind them, including neural networks and deep learning. Explore prompt engineering techniques to maximise your results. Practise evaluating and improving model performance by fine-tuning a pre-trained language model. Explore how to deploy generative AI models.
Unit 4
Big Data Fundamentals With Machine Learning
New data of varying types are constantly being produced at a staggering rate through the increased use of technology from individuals and organisations. From images, to text, to sensor data, and more, Data Scientists must be capable of handling, organising, and analysing these massive quantities of data. Together with machine learning, big data can be used to provide unique insights and powerful capabilities, like natural language processing and more. In this unit, you will be exposed to the world of big data, and leverage industry tools to learn and apply key concepts related to big data, machine learning, and deep learning.
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- Key Skills:
- Cloud Fundamentals
- Recommender Systems
- Big Data Analysis
- Machine Learning
Learn Big Data Fundamentals
Big data sets are often diverse, containing information from different sources and in different formats. This reality requires a number of individuals and different technologies to effectively manage big data. You'll gain a strong foundation around big data, and explore the technology, architecture, people and processes used to work with big data in the real world.
Perform Meaningful Big Data Analysis
Practise using industry tools including Amazon Web Services, Hadoop and more to set up big data architecture and work with big data sets. You'll learn methods to manipulate and organise data to perform meaningful analysis, and solve data problems.
Explore Diverse Machine Learning Techniques & Models
Building on your understanding of machine learning, you'll explore new techniques, concepts, and models and when to use them. Some of these topics include; recommender systems, machine learning pipelines, automation, deep learning, and machine learning as a data science product.
Unit 5
Professional Development
Data science is a diverse field, requiring a number of different skills. In order to provide value in the workplace, Data Scientists need some complementary knowledge to support their core skills. In this unit of BrainStation's Data Science bootcamp, you'll round out your learning experience by exploring important data science topics including design thinking, Agile, and more. Understanding these topics and developing skills around them will help you collaborate with others, communicate with key stakeholders, and integrate your capabilities into larger projects. In this unit, you'll also complete your Capstone Project, and dive into preparing for your new career with BrainStation's Career Accelerator Programme.
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- Key Skills:
- Agile
- Data Science Portfolio Development
- Design Thinking
- Whiteboarding
- Career Acceleration
- Presentation & Communication
Learn Essential Skills for the Workplace
Successful Data Scientists are able to approach problems creatively, work with teams, and clearly communicate key insights. You'll explore the importance of Design Thinking to help you approach data science problems, and learn about the Agile Methodology – commonly used by digital and technology teams. You'll also build your presentation skills and learn how to capture the attention of a diverse audience to deliver key insights.
Explore Ethics for Data Science
Data is highly sensitive and needs to be handled appropriately and analysed correctly to provide accurate results. Therefore, Data Scientists have a responsibility to understand the ethics of their work. Through case studies you'll learn about the importance of ethics in data science, and explore key concepts that should be considered in data projects.
Prepare to Launch Your New Career
Go deep on professional development and prepare to launch your new career with BrainStation's Career Accelerator Programme. Build your professional presence using Github to host your work and create a portfolio, and prepare to present yourself and your work to potential employers.
Demo Day: Meet Employers and Build Your Network
Demo Day is a celebration of everything you've learned and accomplished in your bootcamp. It's where you'll showcase your final project among your peers, hiring managers, data professionals, and alumni from cutting-edge companies that need digital skills.
View Tuition, Financing Options, and More in the Programme Package
View the Programme Package to access:
- Tuition details
- Scholarships and financing options
- Application process
Top Rated Bootcamp By Students & Employers
BrainStation has once again shown that they are modernising education for future career professionals. Getting to see the amazing work accomplished by their diverse and talented students has been an extraordinarily inspiring experience.
Dan Silveira
180 Days of Career Services
We're in it together. During your Data Science bootcamp and beyond, work with BrainStation's dedicated Career Success team to help launch your new data science career track in a structured and accountability-based environment. In addition to meeting with your peers and our Career Success team members, you'll have access to a variety of world-class career services that have been proven with thousands of BrainStation bootcamp graduates.
Career Support From Day 1
Your career transformation begins on day 1. Kick off your programme with goal-setting and career prep that sets you up for success. From the first day, throughout the programme and beyond, we're with you to transform your career.
Hands-On Workshops Throughout the Data Science Programme
Your BrainStation bootcamp is designed with career success in mind, and includes regular workshops that prepare you to tell your story and master your data science job search with resume, LinkedIn, and interviewing support and guidance.
1-on-1 Support When You Need It
Everyone's data science career track journey is different, so you'll have 1-on-1 support from BrainStation's dedicated Career Success and career coach team to direct your career prep and help you navigate your own unique career transformation.
BrainStation provided me with the essential programming skills and a strong foundation in basic data science theories and knowledge. Furthermore, I was given clear directions on how to position myself strategically during the job hunt process.
Hannah Cheng
Data Scientist at EllisDon
What Our Graduates Are Saying
Daria Aza
Associate Data Analyst at Manulife
The most valuable skills I learned are related to time management and being resourceful. I can now understand the root of any problem on the fly and quickly find a solution for it, even if it involves learning new things rapidly to complete the task. . . .
I have my first real job in the industry and I'm applying everything I've learned at BrainStation!
Read Full Testimonial
Tom Keith
Data Scientist at Bell
The highlights were the skills learned, projects completed, and confidence gained to start a new career in data along with being surrounded by such amazing like-minded peers is very inspiring and motivating. . . Visit the campus on Demo Day and witness for yourself what is possible with the programme. The passion the students have for their projects is inspiring.
Read Full Testimonial
Hannah Cheng
Data Scientist at EllisDon
I really appreciated the Instructors' patience and expertise in helping the students get through a steep learning curve. Especially our Associate Instructor. . . he created a really a great learning experience and spent extra hours to help us with our capstone projects. . . .
BrainStation provided me with the essential programming skills and a strong foundation in basic data science theories and knowledge. Furthermore, I was given clear directions on how to position myself strategically during the job hunt process.
Read Full Testimonial
Join our growing community of 15,000+ alumni.
Data Science FAQs
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What is the difference between data science and data analytics?
Data Scientists, generally speaking, have more technical knowledge and expertise than Data Analysts. Because of this, data science positions are typically more senior in nature compared to roles that involve data analysis skills.
In BrainStation's latest Digital Skills Survey, respondents working in data science said the objective of their work was the optimization of an existing platform, product or system (45 percent), or the development of new ones (42 percent). In unpacking their responses, we found that the work of “optimising existing solutions” tends to fall to Business Analysts and Data Analysts, while the higher-order work of “developing new solutions” more often falls to Researchers and Data Scientists. What this suggests is that Data Scientists, who typically have more experience and more specialised expertise, are more likely to be involved in decision-making at a leadership level.
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Will I earn a data science diploma from this bootcamp?
Yes, when you complete the Data Science bootcamp, you will earn a BrainStation Data Science diploma, which can boost your LinkedIn profile and resume, helping you stand out in the job market when starting a new career in data science.
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What are the outcomes for Data Science bootcamp graduates?
Speak to a learning advisor to get more information about bootcamp graduate outcomes. We do not guarantee that graduates will get a job, but we are proud to have launched thousands of graduates’ careers. We offer comprehensive Career Success programming and believe that students who invest both during and after the bootcamp will have the best outcomes.
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What payment options do you offer?
BrainStation offers some of the most competitive payment options for a Data Science bootcamp, with a range of flexible plans and scholarship opportunities.
These include:
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Monthly payment instalments
Allowing you to split your tuition into smaller monthly payments.
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Employer sponsorship
Get your tuition reimbursed by your employer.
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Scholarships
We offer a range of scholarships to make learning Data Science more accessible.
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Monthly payment instalments
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What kind of backgrounds do people have that take this data science bootcamp?
Once admitted to BrainStation's Data Science bootcamps, you can expect to learn from experienced data scientist Educators with experience in the field, and to collaborate alongside like-minded, ambitious professionals who have taken the step to transform their skills for a new career in data science.
Professional backgrounds vary quite a bit in the Data Science programme , as demand for Data Scientists and data science skills has surged across a range of fields and industries, including finance, marketing, mathematics, engineering, statistics, web development, IT, and more.
80 percent of BrainStation students have a post-secondary education, with 20 percent having earned a Master's degree or PhD.
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What tools and programming languages do we learn?
Students in Data Science bootcamps use Python, R, Hadoop, Tableau, and more to learn statistical methods and data modelling, including regression techniques, machine learning, deep learning, data visualisation, and more.
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What is the difference between this and the part-time Data Science course?
BrainStation's Data Science bootcamps are intensive learning experiences designed to transform your skillset and help you launch a new career in data. Throughout the Data Science programme, Data Science bootcamp students develop and complete five projects including one major capstone project portfolio piece, using real-world data science and data visualisation techniques. By the end of the Data Science programme, graduates will have the skills, experience, and portfolio needed to land a job in data, and will have completed career prep to set them up for success.
BrainStation's Data Science courses, on the other hand, are flexible, professional development courses offered part-time, over 4 or 8 weeks. Taught by industry experts, the Data Science course is a project-based, hands-on learning experience, allowing you to develop data science skills and learn the latest data tools and technologies.
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What kind of jobs can this bootcamp get me?
Because the work Data Scientists do touches so many different industries and disciplines, the roles within a data science career go by many different names, including:
Data Scientist
Data Analyst
Data Architect
Data Engineer
Statistician
Database Administrator
Business Analyst
Data and Analytics Manager
Researcher
Machine Learning Engineer
Quantitative Analyst
Many other variations exist and these will continue to evolve as data science becomes more prevalent.
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What kind of career services do I get?
BrainStation's Career Success and career coach team is dedicated to creating a learning experience within this data scientist programme that extends far beyond the classroom, providing a framework for success built on insights and input from technical recruiters, career coaches, BrainStation Educators, and alumni.
Through BrainStation's Data Science bootcamps, the team will support you on your data science career track and help you refine your portfolio, connect you with industry professionals, prepare you for the career search and interview process, and showcase your work to peers and hiring partners.