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9 - 10.30 AM
Grab a coffee and start every morning with an engaging & interactive lecture, before putting what you’ve learnt into practice.
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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 our Data Science bootcamp looks like
Check out our curriculum week after week.
Prepwork: get ready to start the bootcamp!
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
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
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.
- 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
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
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.
- 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
- 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)
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
- World embedding for sentiment analysis or text auto-completion
Project weeks
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 15,000 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
Prepwork: get ready to start the bootcamp!
Our Flex part-time Data Science Bootcamp is a fully remote program that requires online study. To ensure you are thoroughly prepared, you must first complete ~40 hours of intuitive and interactive online learning. This prep work will ensure that you have the necessary foundation in Python and mathematics before the bootcamp begins.
- Setup your learning environment (notes, text editor, etc.)
- 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
- Study curated resources from Le Wagon to build a solid foundation
Data Analysis
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
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.
- 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
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
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.
- 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
- Dense neural network for fraud transaction detection
- Transfer learning for image classification
- Auto-encoders for image compression and denoising
- Recurrent networks for wheather forecasting
- World embedding for sentiment analysis or text auto-completion
Machine Learning Engineering (MLOps)
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
- World embedding for sentiment analysis or text auto-completion
Online Projects
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 a live demo of model predictions
- Create an in-depth analysis of a business dataset
- Replicate latest AI research papers with Big Models!
Career Weeks: start your career in data science!
Meet online with 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 15,000 alumni and 985+ hiring partners
What you will do in practice
- 1:1 online coaching
- Review of CV and cover letter
- Technical interviews preparation
Need more details about our Data Science bootcamp?
Understand the goal of the bootcamp
Get our syllabus week by week
Understand our methodology
4.98 / 5
2259 reviews
4.98 / 5
2301 reviews
4.9 / 5
714 reviews
Download our Data Science syllabus
An immersive program that accelerates
your tech skills in weeks
Passionate teachers, acclaimed methods & real-world skills
- Small cohorts with 1 teacher for 7 students
- Practice on real tech projects with motivated peers
- Get real-time answers to never be stuck
- Keep lifetime access to Le Wagon's learning platform
- Design and pitch your final project in teams
4.98 / 5
2259 reviews
4.98 / 5
2301 reviews
4.9 / 5
714 reviews
-
"If you are looking for a bootcamp that offers a comprehensive curriculum, a great learning environment and incredible post-bootcamp career support then Le Wagon is for you!"
Joseph Gulay
Now Data Analyst at Ernst & Young
-
"It is stunning how much you learn in only 9 weeks, not only web development but also how to challenge yourself and grow as a person!"
Carolina Cota
Now Backend developer at N26
-
"Only two months after finishing the Bootcamp, I landed my first job as a Junior Software Engineer. That would not have been possible without the amazing career support from Le Wagon’s staff."
Mathieu Longé
Now Software Engineer at 99designs
-
"Le Wagon is a great way to get into tech and learn a new skill with good teachers to support your journey and definitely don’t be shy to ask 100 questions like I did."
Ștefania-Ella Centea
Now Junior Product Manager at ASDA
-
"After 3 years working in Investment Banking, I decided to update my skill-set with some tools that I could use for whatever my next professional challenge would be."
Ayelen Klas
Now Sr. Growth & Operations Manager at Razor Group
-
"I expected a lot from Le Wagon for my Data Science formation and the global experience was even better: the content of the formation and the custom learning platform were really well structured and all the people at Le Wagon very helpful."
Josselin Grouas
Now Data/IA Manager Consultant at IBM
-
"The complexity of the final project that I carried out with a team of classmates made me see how much my skills improved during the bootcamp. I highly recommend it."
Rafael Knabben
Now Data Quality Analyst at ResearchGate
-
"Le Wagon truly changed my life with coding. Coming from a sales background, it enabled me to acquire the technical knowledges to start a developer career."
Isabelle Ferrier
Now Web Developer at amlconsult GmbH
-
"I was writing code, cleaning data and building data pipelines with fluidity. I also really enjoy the fact that Le Wagon is here to help you in your job search after the bootcamp."
Cyril Aubry
Now Jr. Data Analyst at N26
-
"In 9 weeks, Le Wagon transformed me from a TV screenwriter into a developer and helped me find not just a dream job, but an actual dream career: one in which I feel valued, good at what I do, and work from wherever suits me best."
Martinho Hoffman
Now Python Developer at Zyte
-
"Teachers here are very pedagogical, they all take the time to make sure students understand key concepts, bring concrete examples to help. They were ready to explain and re-explain, not counting their time."
Jordan Luong
Now Full-stack Developer at Shippio
-
"Le Wagon staff will ensure that you comprehend every concept, learn how to properly use Data Science tools and make the most of this amazing experience."
Timothée Filhol
Now Junior Data scientist at Biofourmis
Career services
Land your dream job with our career team
Benefit from personalized coaching, attend job fairs, get prepared for interviews, connect with recruiters.
985+
hiring partners
93%
of graduates find jobs
3 months
on average to find a job
See what our Data Science
graduates do now
Employer Testimonials
-
""We have been partnering with Le Wagon for the past 2 years to bring awesome engineering talent into our emerging talent programs and I am constantly in awe of the high calibre of students they produce - the future of tech is definitely bright with Le Wagons programs!" "
Kerry Callenbach
People & Culture Specialist
Mantel Group
Financing
Do you need help with financing?
Understand your eligibility and learn how to finance your bootcamp.
- Installment plan - Spread out your tuition payments.
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.
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.
Have questions?
Choose the right course for you
Explore your financing options
Preview our learning platform
4.98 / 5
2259 reviews
4.98 / 5
2301 reviews
4.9 / 5
714 reviews
Book a free call with our advisor
Why you should study Data Science in Melbourne
Data Science is so versatile, it can bring value to any industry or basically any other field of research!
With the boom of Big Data, data scientist will be the most in-demand profession in the next 5 years.
Also, did you know... That according to Seek, the average annual salary for Data Scientist jobs in Australia ranges from $115,000 to $135,000?
Events
Start your tech journey by attending a free workshop in Melbourne
In addition to our courses, we host free evening workshops and entrepreneurial talks at our Melbourne campus. Come down and meet us!
How to use Github and effectively work with developers
Limited seats
Online Workshop: Create your landing page in 2 hours
Limited seats
Web Development course in Melbourne
Data Science course in MelbourneLe Wagon Melbourne
41 Stewart St, Melbourne VIC 3121
You can start for FREE! Join a live workshop for web development, data analytics, or UX design.
41 Stewart St, Melbourne VIC 3121
Web Development course in Melbourne
Data Science course in MelbourneLe Wagon Melbourne
41 Stewart St, Melbourne VIC 3121
F.A.Q.
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.
15,000
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
4.98 / 5
2259 reviews
4.98 / 5
2301 reviews
4.9 / 5
714 reviews
Download our Data Science syllabus