Part-time (24 weeks)

In 24 intensive weeks in London, learn all the skills of a Data Scientist. Analyse rich data sets, make complex decisions using data and discover the power of AI & Machine learning to solve real world problems.

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 In 24 weeks, part-time, learn Data Science from Python to advanced Machine Learning at Le Wagon London
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Apr 9, 2022 - Sep 24, 2022 Course in English (£6,900)
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Join an immersive Data Science course

Our part-time Data Science course in London gives you the skills you need to launch your career in a data science team, in 24 weeks studying some weekday evenings and Saturdays. 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.

Le Wagon's Data Science course gives you the data science skills you need to launch your career in any data-related role.
Learn Data Science in 24 weeks
Check out what our alumni have built in their final weeks

Our Data Science curriculum

Our course in London is designed to help you learn Data Science step by step. Use data to provide actionable insights and build a real-world data application to showcase your skills.

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Python for Data Science

Learn programming in Python, how to work with Jupyter Notebook and to use powerful Python libraries like Pandas and NumPy to explore and analyse big data sets. Collect data from various sources, including CSV files, SQL queries on relational databases, Google Big Query, APIs and Web scraping.

Relational Database & SQL

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.

Data Visualization

Make your data analyses more visual and understandable by including data visualisations 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.

Statistics, Probability, Linear Algebra

In London you will learn about 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.

c pulse Statistical inferences

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.

speaker Communication

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.

Preprocessing and Supervised Learning

Learn how to explore, clean, and prepare your dataset through preprocessing techniques like vectorisation. 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).

Generalisation and Overfitting

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.

Performance Metrics

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).

Unsupervised Learning & Advanced Methods

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.

Neural Networks

Unveil the magic behind Deep Learning by understanding the architecture of neural networks (neurons, layers, stacks) and their parameters (activations, losses, optimisers). 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.

Computer Vision

Go further into computer vision with Convolutional Neural Networks, architectures designed to make the most out of images. Improve your model generalisation thanks to data augmentation techniques and implement advanced methods to benefit from state-of-the-art architectures thanks to Transfer Learning methods.

Times-Series & Text data

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.

Deep Learning made easy

Discover the Keras Deep Learning library which enables you 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.

Machine Learning Pipeline

Move from Jupyter Notebook to a code editor and learn how to set up 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.

Machine Learning workflow with MLflow

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.

Deploying to production with Google Cloud Platform

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 into any front-end interface.

Solve real-world problems with Data!

The final weeks of the course will culminate in the delivery of your capstone project! Working collaboratively in small teams, the project will allow you to utilise all the skills you have learned throughout the bootcamp in order to solve a real world data science problem.

  • Collaborate efficiently in teams of 3-4 people on a real data science project through a common Python repository.
  • 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.)
  • Put into practice all the tools, techniques, and methodologies covered in the Data Science Course.
  • Invent, pitch, design, code, and deploy your fully functioning Data Project, to be used in real-life scenarios and as a portfolio-ready application to showcase your new data science skill set.

Admission & prep work

Our Data Science course requires a basic level of Python & Mathematics. As we want all of our students to succeed, you'll be able to test your level and refresh your skills before the Bootcamp starts.

Admission prerequisites in Python & Maths
  • Python prerequisites

    You'll need to be comfortable with data types & variables, conditions, loops, functions and data structures (List & Dictionary).

  • Mathematics prerequisites

    You'll need a High School level of Maths, meaning you will be comfortable with functions, derivatives, and systems of linear equations.

  • Testing your skills

    After a chat with our Admissions team, you will receive a Python & Mathematics Quiz to help you and the Admissions team better understand your current level in Python & Maths. We'll also provide you with a set of additional free learning resources to help you match the prerequisite level for the Bootcamp.

Post-admission prep work

Once you have been accepted onto the Data Science Bootcamp (congrats!), you'll receive ~ 40h of online learning resources. We require all of our students to complete this before the Bootcamp starts, either at their own pace or during our Data Prep Week.

The Data Prep Week takes place the week before the official start date of the Bootcamp. This is an additional week of interactive online learning designed to help you get through this content as efficiently as possible and ensure you have the necessary foundations in Python before the bootcamp starts.

Our part-time format

Learn to code in 24 weeks with a tailor-made program adapted to school & public holidays, and above all to your busy schedule.

10:00 AM 05:00 PM
06:30 PM 09:30 PM
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
Homework Watch the lecture to prepare for next session.
Live sessions Pair program with your classmates on coding challenges with the help of our teachers.
Live sessions Pair program with your classmates on coding challenges with the help of our teachers.
Homework Watch the lecture to prepare for next session.
Live sessions Practice all day on challenges and projects.

Consolidate what you've learnt through live-code sessions with your teachers.
☀️
Homework

Watch the lecture to prepare for next session.

Remote

Pair program with your classmates on coding challenges with the help of our teachers on Zoom.

Live sessions (Full day)

Practice all day on challenges and projects.

Consolidate what you've learnt through live-code sessions with your teachers.

A taste of our program in London

Live a unique learning experience every week.

On campus pair-programming sessions
On campus pair-programming sessions

Meet your peers and teachers once a week to work on coding challenges. Learn to think and solve problems like a Data Science professional.

Online lectures and flashcards
Online lectures and flashcards

Watch lectures at your own pace on our online platform. Grasp core concepts and prepare yourself for the next coding session. Consolidate your knowledge on a daily basis playing our Flashcards.

Hiring and networking Events
Hiring and networking Events

Every week, join us for events with entrepreneurs and hiring partners. Create your own network within a thriving tech scene.

Career Week

At the end of the bootcamp, we will organise our Career Week. This week gives you the tools you need to take the next steps in your career, whether it is finding your first job in a Data Science role, exploring career opportunities with your new data skill set, or launching your start-up.

Workshops Workshops

Benefit from a combination of panel discussions, workshops, presentations, and assignments to help you find the right career path.

Becoming job-ready Becoming job-ready

Prepare your personal profile, complete job applications, prepare for technical challenges, and make a game plan for after the bootcamp!

Inspiration Inspiration

Hear from alumni about their post-Bootcamp journeys and what a typical day looks like in their new careers.

Custom-made Custom-made

You can join any workshops or watch any tutorials that you are interested in. You create your own career week according to our interests and objectives

Timetable for the week
Monday
  • Discover career paths
Tuesday
  • Prepare for a job application
Wednesday
  • Prepare for technical challenges
Thursday
  • Apply for jobs
Friday
  • Game plan post bootcamp

Passionate teachers

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 Westerman
Chris Westerman

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
Lucien George
Lucien George

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 an Engineering Manager at Le Wagon.

more about Lucien

Network and learning platform

London's 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.

Slack icon Slack groups

Get tips and advice from professional data scientists & data analysts, access exclusive job and freelance opportunities from entrepreneurs & developers.

Online classroom

Access our online education platform at any time after the course: you will find all data science lectures, screencasts, challenges and flashcards.

Tech community

Benefit from our global community of 12,945 alumni working in data-related roles, but also entrepreneurs, developers and product managers all over the world.

Icon tutorials Global presence

Our different courses are running in 44 campuses all over the world: wherever you go, you belong to the Le Wagon community!

Community and tools for life

Find a data job in the best business & tech companies in London

Once the course ends, you benefit from our career services. We help you meet with the best recruiters in London and connect with relevant alumni.

microsoftwordCreated with Sketch. Career Playbook

Access a complete guide to kick-start your Data Science career in London after the course: boost your portfolio, find your dream job, leverage on our 12,945 alumni community.

myspaceCreated with Sketch. Career Events

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.

buymeacoffeeCreated with Sketch. Alumni Coaching Sessions

Our Data Science Course alumni love to share their experiences with more recent graduates. They explain how Le Wagon helped them find their dream role in Data Science and share insights into how they used their new data skill sets to accelerate their careers in various sectors, such as marketing, finance, healthcare and academic research.

wechatCreated with Sketch. Career Intros

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.

Our web development course alumni get hired by the best companies

Where our alumni work in data in London

The best companies partner with Le Wagon and hire our alumni as Data Scientists, Data Analysts, Product Managers or Data Engineers.

BCG Digital Ventures Hired 6 graduates
+4
Doctolib Hired 9 graduates
+7
Facebook Hired 3 graduates
+1
Getaround Hired 6 graduates
+4
Google Hired 5 graduates
+3
Uber Hired 2 graduates

Find the right financing option for you

Find out if you are eligible for special offers in London.

Pay in instalments while you study
Pay in instalments while you study

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.

Web Development: £7,000

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.

Data Science: £7,400

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 here
Spread the cost of your tuition over time with Coursebud

Coursebud helps you search multiple lenders to find the one that works for you - enabling you to pay back your tuition in manageable monthly instalments.

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Le Wagon London Scholarship

This Scholarship programme aims to help train and support people coming from historically underrepresented groups in STEM disciplines to start or boost their career in the tech sector.

We're looking for a future founder or one to watch in the tech industry as a software developer, data scientist, product manager, entrepreneur or freelancer - the choice is yours after the Bootcamp!

The Le Wagon London Scholarship programme is open for 2022.

The most acclaimed Data Science Bootcamp and courses

Le Wagon is the #1 ranked coding bootcamp on Switchup Coursereport logo

Le Wagon has 2164 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. Behind these reviews are hundreds of people around the world who have had a life-changing experience joining our program, which 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 2164 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 44 cities we run our coding bootcamps in.

Campus Le Wagon London

Data Science course in London
Le Wagon London
Shoreditch Stables, North, 138 Kingsland Rd, London E2 8DY

Any questions about our program in London

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.

How are your students learning at the moment?

Our London Campus is currently open. All of our Le Wagon London students (Full-time & Part-time) have the option to work on campus.

We have been running Hybrid Bootcamps in London since mid-2020, where students can decide if they want to learn either on campus, learn remotely, or a mixture of on campus and remote learning.

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.

What Career Support is there after the Bootcamp?

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 your LinkedIn profile, searching for jobs, mastering technical interviews, tackling tech tests and more... All 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.

Read 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.

What is the application process and when should I apply?

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 Quiz after your interview

We will then review your application as a team and let you know if you have been successful in being accepted onto the Bootcamp within 24 hours!

We start Bootcamps every quarter, and open applications roughly 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.

How does the Part-Time Bootcamp work?

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.

What equipment do I need to join the Bootcamp?

It is essential 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 recommend sticking with whatever laptop and operating system you are the most comfortable with and quickest at using!

Are your Bootcamps suitable for beginners?

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, marketers, 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.

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Want to go further?

Next London Data Science course (part-time coding bootcamp) starts on Apr 9, 2022

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