Overview
Acquire advanced data skills, master Machine Learning & AI, and launch your career as a Data Scientist, Analyst, AI Engineer, Data Manager, and more.
Learn essential data analysis methods and tools
Master Machine Learning and Deep Learning
Create AI solutions and advanced predictive models
Build a solid portfolio and learn to work in a data team
You will master these programming languages and tech tools:
Python
SQL
Jupyter
Pandas
Git
Docker
Scikit-Learn
Hugging Face
OpenAI
Course Description & Learning Outcomes
Gain the skills needed for a successful data science career. Learn to create Machine Learning and AI models, and deploy them into production while working with a team.
Preparation work
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 programming and maths before the bootcamp starts.
Python Introduction - Understand the fundamentals of Python
It’s highly recommended that you join our online pre-bootcamp Python introduction. During this time, collaboratively engage with your instructors in a live online setting to understand the fundamentals of Python. Familiarize yourself with technical terminology, key concepts and the right learning mindset before your first day of the bootcamp.
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.
Decision Science - 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.
Machine Learning - 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.
Deep Learning - 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.
ML Engineering - Train your model
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.
Generative AI - Leverage AI in your projects
Through a series of live lectures, harness the capabilities of Generative AI tools to streamline your coding workflows and explore vital ethical considerations in AI. Gain insights into making complex AI models comprehensible to stakeholders and focus on the implementation of effective CI/CD pipelines.
Project Weeks - 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!
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.
Recommended Prerequisites
To apply for the data science bootcamp, you should have a solid foundation in programming and mathematics.
But the most important thing is that you are motivated to embark on this new tech adventure.
Schedule
End Date: 09 Sep 2024, Monday
This is an immersive bootcamp, held part-time over 2 weekday evenings online from 7pm to 10pm and on campus on Saturdays from 9am to 6pm.
Location: 20 Collyer Quay, Level 23, 049319 and Online
