In 9 intensive weeks in London, learn Data Science from Python to advanced Machine Learning, get all the skills to join a Data Science team and boost your career.
Some of our upcoming courses in London can be followed remotely. After you complete your application, the admission manager will be in touch shortly to give you all the necessary information.
Our full-time Data Science in London course gives you the skills you need to launch your career in a Data Science team in only 9 weeks. From Pandas to Deep Learning, you will finish the course knowing how to explore, clean and transform data into actionable insights and how to implement Machine Learning models from start to finish in a production environment, working in teams with the best-in-class tool belt.
Our course is designed to make you learn Data Science step by step, starting with the basic data toolkit in Python and Mathematics to the complete implementation and deployment cycle of Machine Learning algorithms.
Our Data Science course is very intense. To save time and nail it from the beginning, our students must complete an online preparation work before starting the bootcamp. This work takes around 40 hours and covers the basics of Python, the pre-requisite language of the course, and some mathematical topics used every day by data scientists.
Learn programming in Python, how to work with Jupyter Notebook and to use powerful Python libraries like Pandas and NumPy to explore and analyze big data sets. Collect data from various sources, including CSV files, SQL queries on relational databases, Google Big Query, APIs and Web scraping.
Learn how to formulate a good question and how to answer it by building the right SQL query. This module will cover schema architecture and then dive deep into the advanced manipulation of SELECT to extract useful information from a stand-alone database or using a SQL client software like DBeaver.
Make your data analyses more visual and understandable by including data visualizations in your Notebook. Learn how to plot your data frames using Python libraries such as matplotlib and seaborn and transform your data into actionable insights.
Understand the underlying math behind all the libraries and models used in the bootcamp. Become comfortable with the basic concepts of statistics & probabilities (mean, variance, random variable, Bayes’s Theorem, etc.) and with matrix computation, at the core of numerical operations in libraries like Pandas and Numpy.
You'll learn how to structure a Python repository with object-oriented programming in order to clean your code and make it re-usable, how to survive the data preparation phase of a vast dataset, and how to find and interpret meaningful statistical results based on multivariate regression models
Data analysts are meant to communicate their findings to non-technical audiences: You will learn how to create impact by explaining your technical insights and turn them into business decisions using cost/benefits analysis. You'll be able to share your progress, present and compare your results to your teammates.
Learn how to explore, clean, and prepare your dataset through preprocessing techniques like vectorization. Get familiar with the classic models of supervised learning - linear and logistic regressions. Learn how to solve prediction and classification tasks with the Python library scikit-learn using learning algorithms like KNN (k-nearest neighbors).
Implement training and testing phases to make sure your model can be generalised to unseen data and deployed in production with predictable accuracy. Learn how to prevent overfitting using regularization methods and how to chose the right loss function to improve your model's accuracy.
Evaluate your model's performance by defining what to optimise and the right error metrics in order to assess your business impact. Improve your model's performance with validation methods such as cross validation or hyperparameter tuning. Finally, discover a powerful supervised learning method called SVM (Support Vector Machines).
Move to unsupervised learning and implement methods like PCA for dimensionality reduction or clustering for discovering groups in a data set. Complete your toolbelt with ensemble method that combine other models to improve performance, such as Random Forest or Gradient Boosting.
Unveil the magic behind Deep Learning by understanding the architecture of neural networks (neurons, layers, stacks) and their parameters (activations, losses, optimizers). Become autonomous to build your own networks, especially to work with images, times and text, while learning the techniques and tricks that make Deep Learning work.
Go further into computer vision with Convolutional Neural Networks, architectures designed to take the most out of images. Improve your model generalization thanks to data augmentation techniques and implement advanced methods to benefit from state-of-the-art architectures thanks to Transfer learning methods.
Get comfortable into managing sequential data and text (sequence of words) by transforming them into appropriate inputs. Leverage the power of Recurrent Neural Networks to forecast future values and perform valuable Natural Language Processing.
Discover the Keras Deep Learning library which enables to prototype easily while having the flexibility to tune precisely your neural network. Moreover, Google Colab will greatly speed up the computational time thanks to dedicated GPUs.
Move from Jupyter Notebook to a code editor and learn how to setup a machine learning project in the right way in order to quickly and confidently iterate. Learn how to convert a machine learning model into a model with a robust and scalable pipeline with sklearn-pipeline using encoders and transformers.
Building a machine learning model from start to finish requires a lot of data preparation, experimentation, iteration and tuning. We'll teach you how to do your feature engineering and hyperparameter tuning in order to build the best model. For this, we will leverage a library called MLflow.
Finally, we'll show you how to deploy your code and model to production. Using Google Cloud AI Platform, you'll be able to train your model at scale, package it and make it available to the world. Cherry on top, you will use a Docker environment to deploy your own RESTful Flask API which could be plugged to any front-end interface.
You'll spend the last two weeks on a group project working on an exciting data science problem you want to solve! As a team, you'll learn how to collaborate efficiently on a real data science project through a common Python repository and the Git flow. You will use a mix of your own datasets (if you have any from your company / non-profit organisation) and open-data repositories (Government initiatives, Kaggle, etc.). It will be a great way to practise all the tools, techniques and methodologies covered in the Data Science Course and will make you realize how autonomous you have become.
From morning lectures to evening talks, every day is action-packed.
Grab a coffee and start every morning with an engaging & interactive lecture, before putting what you’ve learnt into practice.
Pair up with your buddy for the day, and work on a series of programming challenges with the help of our teaching staff.
Learning to code is very intense, so it’s important to take a break and relax during our yoga classes, which run at least once a week.
Review the day’s challenges and get an overview of upcoming lessons during live code sessions.
Be inspired and get priceless advice from successful entrepreneurs invited for exclusive talks.
Since day one, we’ve taken teaching seriously. Great teachers inspire us to connect to topics on a profound level. Experience as a developer alone doesn’t necessarily make one an effective teacher — that’s why we’re passionate about finding not only great engineers, but deeply committed, experienced teachers.
Chris studied Business and worked for 8 years in Hotel Revenue Management. After moving to London he turned his focus to the technical side of his role and completed both our Web Dev & Data Science Bootcamps before joining the core team!
more about Chris
Ben studied and worked in IT for 11 years, working closely with developers. In 2017, he realised he wanted to become one and never looked back! He joined the team full-time as a Teacher & Engineer, and now leads the Data Science program in the UK.
more about Benjamin
Having graduated from an MSc Computational Biology in 2014, Blair spent the last 6 years building his skillset as a Data Scientist. He's now joined Le Wagon, as well as being a meetup organiser, open source contributor and musician.
more about Blair
Lucien studied Software Engineering at McGill University before attending our Bootcamp in London. He then worked as a Developer at a digital agency, before joining our team full-time. He is now a Lead Data Science Teacher and Engineer at Le Wagon.
more about LucienOur Data Science course is just the beginning of the journey. Once you graduate, you belong to a global tech community and have access to our online platform to keep learning and growing.
Get tips and advice from professional data scientists & data analysts, access exclusive job and freelance opportunities from entrepreneurs & developers.
Access our online education platform at any time after the course: you will find all data science lectures, screencasts, challenges and flashcards.
Benefit from our global community of 10,494 alumni working in data-related roles, but also entrepreneurs, developers and product managers all over the world.
Our different courses are running in 43 campuses all over the world: wherever you go, you belong to the Le Wagon community!
Once the course ends, you benefit from our career services. We help you meet with the best recruiters and connect with relevant alumni.
Access a complete guide to kick-start your Data Science career after the course: boost your portfolio, find your dream job, leverage on our 10,494 alumni community.
Attend our job fairs and networking events, meet with the best tech companies and receive offers by recruiters looking for talent in data-related roles.
Our data science course alumni love to share their experiences with fresh graduates: they explain how they found their job as Data Scientist, Data Analyst or Data Engineer.
Our local teams know their alumni and hiring partners, what they are up to and what they are looking for. They introduce you to the right people depending on your goal.
The best companies partner with Le Wagon and hire our alumni as Data Scientist, Data Analyst or Data Engineer.
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Hired 6 graduates
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Find out if you are eligible for special offers in London.
A deposit of £2,500 is due upon signature of the contract, and the remaining balance of £4,000 is paid 1 week before the course start date.
A deposit of £2,500 is due upon signature of the contract, and the remaining balance of £4,400 is paid 1 week before the course start date.
Pay your tuition in instalments, where the deposit is paid to secure your seat on the Bootcamp, and the remaining balance is paid over 6 monthly instalments. There is a £500 management fee associated with this option.
A deposit of £2,500 is due upon signature of the contract, and the remaining balance is paid in 6 monthly instalments of £750 each, starting one week before the course start date.
A deposit of £2,500 is due upon signature of the contract, and the remaining balance is paid in 6 monthly instalments of £816.70 each, starting one week before the course start date.
*To be eligible for the instalment plan, you must: be over 18 years old; be a European Citizen; have a UK Bank Account; not have any convictions for financial crimes; successfully pass the credit check; and be successfully enrolled in the Training Programme.
More information, including eligibility criteria, is available hereCoursebud helps you search multiple lenders to find the one that works for you - enabling you to pay back your tuition in manageable monthly instalments.
Find out more here
Le Wagon has 1953 reviews with an average grade of 4.98/5 which makes it the most acclaimed coding bootcamp worldwide on Switchup according to student reviews! Whilst these reviews make us proud, above all they make us happy. Behind these reviews are hundreds of people around the world who have had a life-changing experience joining our program, that has opened new doors for them. We feel blessed and honoured to have enabled them - and to keep enabling our students - to become autonomous in coding, upskill or change their career, or launch their own startups.
Also, these 1953 reviews are extremely important for us to make sure we’re always meeting the same level of excellence. Having such positive and enthusiastic reviews about our bootcamps is the ultimate proof that we provide the best tech education for all our students, in the 43 cities we run our coding bootcamps in.
If you got here, it means that you have questions about Le Wagon: how to apply, who can join, what you’ll learn… Good! We have the answers.
We have been running Hybrid Bootcamps in London since the summer, where students can decide if they want to learn either on campus, fully remotely, or do a mixture of on campus and remote learning.
Our London campus is currently closed as per the National lockdown, and all current students are learning fully remotely.
We are closely following all advice from the UK Government regarding the ongoing Covid-19 pandemic, and we have strict safety rules in place for those who choose to learn in person.
Please check out our videos for more info on what this looks like: Remote Learning & Hybrid Learning in London.
We have both internal and external processes to help you kick-start your career in Tech after the Bootcamp, including:
Career Week. The week after the bootcamp finishes, we organise a structured Career Week for all graduates. During this week, we organise workshops, talks and masterclasses on creating the perfect CV, updating their LinkedIn, searching for jobs, how to master technical interviews, tackling tech tests and more to help our graduates kickstart their job search, freelancing career or bringing an MVP to market and launching their startup.
We host a Monthly Alumni Stand-up, where we introduce graduates to new hiring partners, and share experiences and resources among our alumni.
Graduates can book in time to speak 1:1 with our Talent Manager, Laura, for ongoing career support anytime during and after the bootcamp. She’ll help you with anything you need, from how to tackle your job search, preparing for interviews, managing offers and salary negotiation, to finding co-founders and fundraising.
We run Events throughout the bootcamp giving you the chance to build your network and discover the London Tech scene. We also host Alumni Discussion Panels, where you can hear about the experience of recent graduates after the bootcamp and get tips on your future career plans.
You will get access to online tools hosted on our learning platform, including hands-on tech-test training and additional learning resources, such as our Intro course to React.
You will also remain part of our Slack community, where new job opportunities are posted on a daily basis.
We recently released our 2020 Jobs Report giving you an overview of career prospects after the Bootcamp. You can also check out our 2019 Career Results Survey as well.
The application process consists of the following steps:
-- Online application available using this link
-- Online interview with our London Admissions team
-- Web Development Bootcamps: Complete this Ruby track within 1 week of your interview
-- Data Science Bootcamps: Complete our online Maths & Python Assessment
-- We will then review your application as a team and let you know if you have been successful in being accepted onto the Bootcamp!
We start Bootcamps every quarter, and open applications about 4 months in advance of the start date. We don't have a hard deadline for applications, it just depends on when spaces fill up, usually around 1 month before the start date.
It is crucial to have a fully functional and recent laptop to make the most of the training.
Tablets are not suitable for the purpose of the Bootcamp
Apple
Apple MacBooks should be no older than 2016 and running on macOS Catalina. Any Apple model is suitable for Bootcamps.
Windows
Windows laptops must be running on Windows 10. Here are some recommended specs:
Minimum specs 🐢(might be a bit slow, but it's workable)
i3 CPU; 8 GB RAM; 64 GO HDD free space
Recommended 👌(should run without complaining)
i5 CPU; 8 GB RAM; 128 GO SSD free space
Comfortable ⚡(no doubt this will run everything without an issue)
i7 CPU; 16 GB RAM; 512 GO SSD free space
We would recommend sticking with what you are the most comfortable with and quickest at using!
Our Part-Time Bootcamps cover the exact same content, line for line, as our Full-Time Bootcamps. The 24-week format is designed to fit around a full time job.
There are three live sessions per week:
-- Tuesday & Thursday evenings from 6.30pm to 9.30pm
-- Saturdays all day from 10.00am to 5.00pm
In addition to these three mandatory weekly live sessions, there are two 1.5 hour lectures to watch online ahead of the Tuesday and Saturday sessions. In total, it is a 15 hour per week commitment.
You can find a detailed description of the course schedule and curriculum on our dedicated pages by selecting the Part-Time course option.
Candidate profiles are very similar to Full-Time candidates, which means we have a mix of career changers, aspiring engineers and developers, project managers and entrepreneurs, among others.
Read more about fitting the Part-Time bootcamp around your life here.
Our Web Development Bootcamp is designed for people with no technical background, which means not having previous coding experience would not impact your ability to complete the course. What our students have in common is a strong willingness to build actionable Tech skills in a short period of time and a desire to learn alongside like-minded people.
Our Data Science Bootcamp requires people to already have strong skills in Maths, and fundamental coding skills in Python.
Motivation and full commitment are the main selection criteria for both bootcamps — as we’ve realised these are the two essential ingredients necessary to turn the Bootcamp experience into a success, no matter your background or previous experience!
People from all kinds of backgrounds join our bootcamps. Aged from 18 - 60, from recent school leavers and University Graduates, to people who have worked 20+ years in completely different fields, including lawyers, hospitality workers, doctors, academics, nurses, teachers, olympians, bankers, engineers, public sector workers and everything in between.
Graduates go on to work as Software Engineers, Back End Developers, Full Stack Developers, Front End Developers, UX Designers, Product Managers, Technology Consultants, Heads of Engineering, CTOs, Data Analysts, Data Engineers, Data Scientists, Data Product Managers, Business Intelligence Analysts, Technical Project Managers, Venture Capitalists and more!
Check out some of our Graduate Stories.
Some of our Graduates go into freelancing and many have gone down the entrepreneurial route, building their own products and founding their own companies.
You can check out some of the companies founded by our Alumni here.
For more questions & answers, you can visit our FAQ section! If you would like to discuss with Le Wagon team, don't hesitate to contact us.
Next London Data Science course (full-time coding bootcamp) starts on Apr 19, 2021
