30h
Get ready to start the bootcamp
Once you’ve been accepted, you'll receive about 30 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 programming and maths before the bootcamp starts.
What you will do in practice:
- How to set up your learning environment (notes, text editor, ...)
- Terminal, Git and OS basic commands
- Python foundations
- Maths foundations (in a fun & intuitive way!)
Software and languages you will learn:
40h
Understand the fundamentals of Data Science
It’s highly recommended that you join our online pre-bootcamp Python & SQL introduction. During this time, collaboratively engage with your instructors in a live online setting to understand the fundamentals. A significant portion of the material covered this week will not be covered at this level of detail during the bootcamp, as the expectation is that participants are already familiar with this material. Familiarize yourself with technical terminology, key concepts and the right learning mindset before your first day of the bootcamp.
What you will learn:
- Understand the fundamentals of Python
- Learn core programming concepts like functions, loops, and conditional statements
- Learn the basics of SQL
- Practice with real coding challenges to build your confidence
Software and languages you will learn:
Python
SQL
56H
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.
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
Software and languages you will learn:
Python
SQL
Jupyter
Pandas
Numpy
Matplotlib
Seaborn
BigQuery
40h
Put yourself in the shoes of a Data Consultant
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.
What you will do in practice:
- 1 week long data consulting challenge based on real data from a marketplace
- Interactive dashboard to communicate your findings effectively
- Individual presentations of your key findings directly to your client
Software and languages you will learn:
88H
Implement the Machine Learning workflow
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.
What you will do 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
Software and languages you will learn:
Scikit-Learn
LangChain
64H
Dive into Deep Learning
Become proficient in neural network architectures and parameters, constructing networks for image, sequence, and text analysis. Dive into AI by coding a transformer from scratch and developing GenAI applications. Gain practical skills with pre-trained "big models" from cutting-edge open-source research.
What you will do in practice:
- Dense neural network for fraud transaction detection
- Transfer learning for image classification
- Recurrent networks for weather forecasting
- Recoding a transformer from 0 to perfectly understand all the architecture
- Fine-tuning your own LLM for your need
Software and languages you will learn:
Tensorflow
Keras
Google Colab
Hugging Face
ChatGPT
Copilot
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.
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
Software and languages you will learn:
Google Compute
BigQuery
ML Flow
Docker
FastAPI
Prefect
Streamlit
Explore additional learning
Alongside your final project, develop core Agile project management skills to structure and deliver technical work effectively. You'll also explore key topics like AI ethics, explainability, and deployment to ensure your solutions are production-ready.
You will learn to:
- Managing technical projects using Agile methodologies
- Understanding the ethical challenges of working with AI
- Discovering techniques for making complex models interpretable
- Gaining hands-on knowledge of Continuous Integration and Deployment in machine learning
80h
Build you own data science project
The project phase is the ultimate experience of the course. Collaborate efficiently in teams of 3 or 4 on a real data science project. 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!
Start your career in data science!
From the moment you embark on your tech journey, our dedicated career services team is there to provide you with tailored guidance throughout and beyond your training. Connect with our vast network of 1000+ hiring partners, benefit from 1:1 coaching and much more!
What you will do in practice:
- Elevate your personal branding & get technical interview training
- Benefit from 1:1 coaching & key alumni Q&A sessions
- Connect with an extensive network of 1000+ hiring partners
- Get a lifetime access to Le Wagon content
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Git
Hugging Face
OpenAI
Copilot
Statsmodel
Plotly
