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.
Pandas
Numpy
Statsmodels
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-Learn
Tensorflow
Google 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.
Git
Docker
MLflow
FastAPI
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
- 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
- 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
- Statsmodels for multivariate linear/logistic regressions
- Packaging and object-oriented programming in Python
- 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
- 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
- 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
- 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
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!
- Preparation for your job search
- Connection to our 20,000+ 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!
Need more details about our Data Science bootcamp?
Understand the goal of the bootcamp
Get our syllabus week by week
Understand our methodology

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!
Suggested requirements
Mathematics: you'll need a High School level of Maths, meaning you will be comfortable with functions, derivatives, and systems of linear equations.
Book an interview with our enrolment advisor
Pass our technical quiz
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
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.
F.A.Q.
- 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)
- 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
- 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 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!)
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
