BOOTCAMP

Change your career with
our Data Science course

Explore the fundamentals of data science and land your dream job with the #1 ranked bootcamp in the world.

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Course info

Master the fundamental skills of a Data Scientist
in just a few weeks

✔

Data Analytics Toolkits

Master the fundamental tools of programmatic data-analysts: Python as a backbone, SQL for queries and Jupyter Notebooks for visualization.

  • Python
  • SQL
  • Jupyter
  • Matplotlib
✔

Decision Science

Leverage statistics to build advanced analyses and take well-informed business decisions: statistical inferences, hypothesis testing, multivariate regression and confidence intervals.

  • PandasPandas
  • NumpyNumpy
  • StatsmodelsStatsmodels
✔

Machine Learning & Deep Learning

Master Machine Learning and Deep Learning workflows (data preparation, model selection, evaluation, and fine-tuning) and understand mathematical concepts and numerical implementations behind models.

  • Scikit-LearnScikit-Learn
  • TensorflowTensorflow
  • Google ComputeGoogle Compute
✔

ML Engineering & Team Projects

Package your models into replicable Python code that can be trained on big data in the cloud, using virtual machines and online databases. Monitor & retrain models when needed, and expose them to the world through APIs.

  • GitGit
  • DockerDocker
  • MLflowMLflow
  • FastAPIFastAPI

You can start for FREE! Join a live workshop for web development, data analytics, or UX design.

What you will learn in practice

You will learn Data Science through 6 modules, either full-time for 2 months or part-time for 6 months.

Prepwork: get ready to start the bootcamp!

40h

Once you’ve been accepted, you'll receive about 40 hours of online learning resources, carefully curated by Le Wagon to be intuitive and interactive. This prepwork will ensure you have the necessary foundations in Python and maths before the bootcamp starts.

  • Setup your learning environment (notes, text editor, ...)
  • Terminal, Git and OS basic commands
  • Python foundations 
  • Maths foundations (in a fun & intuitive way!)

What you will do in practice

  • 40 hours of online tutorials
  • Curated resources from Le Wagon to gain solid foundations

Data Analysis

80h

Learn Python for data science: extract data from relational databases, manipulate big data matrix and build visualizations. Understand key maths concepts for data analysis like statistics & linear algebra.

  • Source data from files, web-scraping, or APIs
  • Manipulate data with Python, Pandas & Numpy
  • Query / store data with SQL & Google Big Query
  • Visualization with Jupyter Notebook, Matplotlib, Seaborn & Plotly

What you will build in practice

  • A database built by scraping data from online bookstores
  • Advanced analysis of football performances in SQL
  • Visual dashboard connected to stock-market APIs

Decision Science

40h

Put yourself in the shoes of a data consultant, and learn how to survive the data preparation phase of a vast dataset. Extract insights by interpreting statistical results based on multivariate regression models, hypothesis testing, and confidence intervals.

  1. Statsmodels for multivariate linear/logistic regressions
  2. Packaging and object-oriented programming in Python
  3. Notebook-based presentations with interactive graphs

What you will build in practice

  • 40h-long data consulting challenge based on real data from a marketplace
  • Individual presentations of your key findings to your client

Machine Learning

80h

Implement the Machine Learning workflow with Scikit-Learn (data preparation, feature engineering, model selection, evaluation, and fine-tuning) and understand maths intuitions and numerical implementations of ML models.

  • Scikit-learn and XGBoost libraries
  • Supervised learning (linear, KNN, SVM, Trees, Ensembles)
  • Unsupervised learning (PCA, K-means, t-SNE, DBSCAN)
  • Structured data (tabular, time-series with SARIMAX...)
  • Unstructured data (images, text with Naive-Bayes, Tf-idf, LDA...)

What you will build in practice

  • Machine Learning models perfectly fine-tuned to your tasks
  • Pipelines combining data processing and model predictions
  • Image compression model by color clustering 
  • Spam detection algorithms
  • Prediction model for house prices

Deep Learning

40h

Unveil the magic behind Deep Learning! Understand the architecture of neural networks (neurons, layers, stacks) and their parameters (activations, losses, optimisers). Build your own neural networks (dense, recurrent, or convolutional), to work on images, sequences and texts. Learn how to re-use and transfer learning from pre-trained “big-models”  from latest open-source research! Get your hands dirty with auto-encoders, batch data processing pipelines, and GPU training.

  • TensorFlow
  • Keras
  • Google Colab

What you will build in practice

  • Dense neural network for fraud transaction detection
  • Transfer learning for image classification
  • Auto-encoders for image compression and denoising
  • Recurrent networks for weather forecasting
  • World embedding for sentiment analysis or text auto-completion

Machine Learning Engineering (MLOps)

40h

Turn your best handcrafted models into a replicable python package that can be trained on big data in the cloud, using virtual machines and online databases. Monitor your model performance as new data comes in, retrain it when needed, and expose its predictions to the world via APIs or websites.

  • VS code & command line
  • Google Cloud, Virtual Machines, SSH for the trainer
  • MLflow & Prefect for DAG orchestration
  • Docker & Fast API for the backend
  • Streamlit for the frontend

What you will build in practice

  • ML model for predicting taxi fares, trained on big data on the cloud with GPUs
  • Visual web dashboard showing live predictions (on charts, maps, etc.)
  • Trained models in production capable of self-healing

Project weeks

80h

Projects Phase is the ultimate experience of the course. Collaborate efficiently in teams of 3-4 people on a real data science project that you will either join or pitch to your class. Use either open-data repositories (government initiatives, Kaggle, Paper with Code, etc...) or bring your own private dataset. With full-time mentoring from expert teachers, let your wildest dream come true!

What you will build in practice

  • Make an app with a live demo of model predictions
  • Create an in-depth analysis of a business dataset
  • Replicate latest AI research papers with Big Models!

Career Week: start your career in data science!

Meet data science experts working in startups or large companies, prepare your CV and do mock interviews to prepare your job search. Go deeper into essential data topics.

  • Preparation for your job search
  • Connection to our 19,000 alumni and 985+ hiring partners

What you will do in practice

  • 1:1 coaching 
  • Review of your CV and cover letter
  • Preparation for technical interviews

Locations

Where would you like to study Data Science?

You can choose to learn Data Science in over 45 locations worldwide or online. Find now your learning destination!

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Need more details about our Data Science bootcamp?

✔

Understand the goal of the bootcamp

✔

Get our syllabus week by week

✔

Understand our methodology

Coursereport

Course Report

4.98 / 5 - 2493 reviews
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Career Karma

4.9 / 5 - 1014 reviews
Download our Data Science syllabus
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Get hired at top tech companies

Le Wagon helps you land your dream job. Our career services guide you at the end of your bootcamp.

N26 Spendesk Qonto Trainline Microsoft BCG Getaround Metaverse Backmarket
Amazon Accenture Doctolib Apple Ernst and Young Shopify Hello Fresh IBM Lydia

985+

hiring partners

93%

employment rate

3 months

on average to find a job

Admission

How to apply to our Data Science bootcamp

Our Data Science course is very complete and intense. But don’t worry, if you don’t have the suggested requirements we will help you get there!

1

Suggested requirements

Programming: you'll need to be comfortable with data types & variables, conditions, loops, functions and data structures.
Mathematics: you'll need a High School level of Maths, meaning you will be comfortable with functions, derivatives, and systems of linear equations.
2

Book an interview with our enrolment advisor

When you apply, we'll get back to you to schedule a 30 minute video interview. We'll talk about your professional project and your motivation.
3

Pass our technical quiz

You will receive a Programming & Mathematics Quiz to help you and the Admissions team better understand your current level.
4

Payment options & prepwork

The last step will consist of finding the most suitable financing option for you. Then, you'll jump into the prepwork which consists of a 40h training.

Ask all your questions to our advisors

Only have one question?

Financing options

Find the right financing
options for you

Finances shouldn't be a barrier to accessing our bootcamps. We're always finding new ways to facilitate payments and fundings.

See your financing options
Student inquiring about available financing options

F.A.Q.

Once the bootcamps ends, you will benefit from our career services.

Our local team will help you prepare for tech interviews, meet the best local recruiters and connect with relevant alumni. You will also have access to a complete guide to kick-start your tech career after the course: boost your portfolio, prepare for technical interviews, leverage on our 10,000 alumni community, but also to lots of useful Slack channels to find jobs or freelance opportunities.

Our local team will introduce you to the right people depending on your goal and you will meet with inspiring alumni who will come back to share their post-bootcamp experiences, like how they found a job, started their own company or freelancing career.

These are some career services we will provide:

  • Networking events, job fairs, career workshops and office hours with alumni or tech recruiters
  • Coaching sessions with our Talent Manager or local alumni
  • Resources our Career Playbook
  • Introductions to our network of hiring partners through our Hiring Newsletter
  • Career week with practical workshops (from building a portfolio to inspiring talks)

Some cities offer specific funding options with local financial partners, like deferred tuition plans, student loans with interesting conditions or Income Share Agreements (ISA). Again, you will find more details about these options on the page of each city on Le Wagon’s website. Also feel free to reach out to the local admission manager to have more details about their local funding options.

At the end of the 9 weeks (full-time) or 24 weeks (part-time), you will have all the skills you need to launch your career in a Data Science team. 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.

You will then have different options:

  • Find a job and join a team as data scientist, data analyst or data engineer
  • Work as a freelancer on data science projects
  • Launch a data science project as an entrepreneur

You need to be 18 to enroll for the course. However, you can apply if you are 17 as long as you turn 18 before the start of the bootcamp.

Data scientists are experts who extract insights from large data sets to help organizations solve complex problems. They work closely with business stakeholders to identify pain points, opportunities for growth, and areas for improvement. 

Their job involves identifying the right data sets, collecting and cleaning them, and analyzing them to identify patterns and trends. They use machine learning, statistical modeling, and artificial intelligence to extract the data the business needs, and help analyze the data and share insights with peers. 

Data scientists present their findings and make recommendations to other members of the organization, and create algorithms and predictive models to extract insights from data. 

Web Development course

You don't need any technical background to join our web development bootcamp. We expect 3 things from our students: be (extremely) motivated, be curious, be social. If this sounds like you, then we'll be more than happy to have you on board if you pass all the selection process.

Data Science course

The Data Science course requires some basic knowledge of programming and mathematics.

  • How much programming do I need to know? Well, you must be comfortable with data types & variables, conditions, loops, functions and data structures like arrays and dictionaries (also called hashes in some programming languages). If you know those topics in other languages than Python (like Ruby, JavaScript, C++, etc.), you have the right programming prerequisites!
  • How much mathematics do I need to know? In order to join our Data Science course, you also need a minimum level in Mathematics and to be familiar with concepts covered in high school's scientific section. We need you to be comfortable with functions, their derivatives & systems of linear equations. To get up to speed, some additional preparation work will be given to you before the bootcamp start to get a refresh of all these concepts as well as more advanced knowledge on linear algebra and statistics.

The job title "Data Scientist" can correspond to very different roles depending on the company (startup, scale-up, big company), the product you're working on and the team you will join. After Le Wagon's Data Science bootcamp, you will be able to apply to data analyst jobs. For data scientist or data engineer jobs, it will depend on the company and their criteria. For instance, some big tech companies (e.g. Airbnb or Facebook) will only accept data scientists profiles with a PhD in Mathematics, so you will not be able to apply to these positions unless you come to our Data Science bootcamp with a strong background in Mathematics already. In lots of smaller companies (like early-stage startups or data agencies) they will accept candidates with solid foundations in data science but less academic background in Mathematics, so they will be very interested in your profile after the course.


The main difference between an academic degree and a bootcamp is that we don't start from scratch and we learn with a lot of practice using modern tools and methods. In an academic curriculum in CS or DS, you will start learning all the theoretical knowledge (e.g. hardware layer of your computer for a CS degree, or advanced concepts of linear algebra and statistics for a DS degree) before moving to applied topics like web development or machine learning. This is only useful if you want to be able to navigate between these layers. However nowadays, you can build almost anything while only mastering the last part. That's why we designed our bootcamps this way. Of course you won't work at Tesla as a software engineer or at Google as a Deep Learning expert (unless you already have a scientific background when joining our bootcamp) but you will be able to work on your own tech products, web applications and data science projects or find a job as a junior developer, data scientist, data analyst or product manager with enough skills and knowledge to get started in your new company and bring value. Of course, that will be your role to keep learning in your new job and become more expert in specific topics.

In most cities, the bootcamp is taught in English.

In French cities, the program is in French. You will have a 1h30 lecture in the morning in French, and a 1h30 live-code in the evening in French as well. So, if you don't understand French correctly, you won't be able to attend the bootcamp in France.

In some other cities (São Paulo, Shanghai, Chengdu, Tokyo) specific sessions are organised in other languages (Brazilian Portuguese, Chinese, Japanese). You can check the language of the next batch on the "Apply" page.

Extra info: all the challenges' instructions and written documentation are in English, so all students must have a good level and understanding or written English, even in cities where lectures are given in another language.

To apply, simply complete the application form on our website by selecting:

  • The course (Web Development, Data Science)
  • The format (9-week full-time, 24-week part-time)
  • The city you're interested in
  • An introduction of why you want to join us and information about your personal project (if you have one!)
This is a quick process which only takes a few minutes. We will then contact you to schedule an interview (either in-person or online) to understand your motivations in more detail and answer any questions you have about our bootcamps.

More than a bootcamp.
Join a global tech network for life.

By choosing Le Wagon, you are joining a supportive community of alumni, teachers, tech recruiters. Benefit from life-long access to the course material, and to our network job offers.

21,000

alumni

45

campuses

1,500

tech experts and professors

93k

meetup members

Need more details about our Data Science bootcamp?

✔

Understand the goal of the bootcamp

✔

Get our syllabus week by week

✔

Understand our methodology

Coursereport

Course Report

4.98 / 5 - 2493 reviews
Switchup

Switchup

4.98 / 5 - 2539 reviews
Careerkarma_white

Career Karma

4.9 / 5 - 1014 reviews
Download our Data Science syllabus
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