In 9 intensive weeks, learn Data Science from Python to advanced Machine Learning, get all the skills to join a Data Science team and boost your career.
Some of our upcoming courses in Lisbon can be followed remotely. After you complete your application, the admission manager will be in touch shortly to give you all the necessary information.
Our full-time data science course gives you the skills you need to launch your career in a data science team in only 9 weeks. From Pandas to Deep Learning, 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.
Our course is designed to make you learn Data Science step by step, starting with the basic data toolkit in Python and Mathematics to the complete implementation and deployment cycle of machine learning algorithms.
Our data science course is very intense. To save time and nail it from the beginning, our students must complete an online preparation work before starting the bootcamp. This work takes around 40 hours and covers the basics of Python, the pre-requisite language of the course, and some mathematical topics used every day by data scientists.
Learn programming in Python, how to work with Jupyter Notebook and to use powerful Python libraries like Pandas and NumPy to explore and analyze big data sets. Collect data from various sources, including CSV files, SQL queries on relational databases, Google Big Query, APIs and Web scraping.
Learn how to formulate a good question and how to answer it by building the right SQL query. This module will cover schema architecture and then dive deep into the advanced manipulation of SELECT to extract useful information from a stand-alone database or using a SQL client software like DBeaver.
Make your data analyses more visual and understandable by including data visualizations in your Notebook. Learn how to plot your data frames using Python libraries such as matplotlib and seaborn and transform your data into actionable insights.
Understand the underlying math behind all the libraries and models used in the bootcamp. Become comfortable with the basic concepts of statistics & probabilities (mean, variance, random variable, Bayes’s Theorem, etc.) and with matrix computation, at the core of numerical operations in libraries like Pandas and Numpy.
You'll learn how to structure a Python repository with object-oriented programming in order to clean your code and make it re-usable, how to survive the data preparation phase of a vast dataset, and how to find and interpret meaningful statistical results based on multivariate regression models
Data analysts are meant to communicate their findings to non-technical audiences: You will learn how to create impact by explaining your technical insights and turn them into business decisions using cost/benefits analysis. You'll be able to share your progress, present and compare your results to your teammates.
Learn how to explore, clean, and prepare your dataset through preprocessing techniques like vectorization. Get familiar with the classic models of supervised learning - linear and logistic regressions. Learn how to solve prediction and classification tasks with the Python library scikit-learn using learning algorithms like KNN (k-nearest neighbors).
Implement training and testing phases to make sure your model can be generalised to unseen data and deployed in production with predictable accuracy. Learn how to prevent overfitting using regularization methods and how to chose the right loss function to improve your model's accuracy.
Evaluate your model's performance by defining what to optimise and the right error metrics in order to assess your business impact. Improve your model's performance with validation methods such as cross validation or hyperparameter tuning. Finally, discover a powerful supervised learning method called SVM (Support Vector Machines).
Move to unsupervised learning and implement methods like PCA for dimensionality reduction or clustering for discovering groups in a data set. Complete your toolbelt with ensemble method that combine other models to improve performance, such as Random Forest or Gradient Boosting.
Get comfortable into managing high-dimensional variables and transforming them into manageable input. Learn classic preprocessing techniques for images like normalization, standardization and whitening. Apply the right type of encodings to prepare your text data for different NLP tasks (Natural Language Processing).
Understand the architecture of neural networks (neurons, layers, stacks) and their parameters (activation functions, loss function, optimizer). Become autonomous to build your own networks like Convolutional Neural Networks (for images), Recurrent Neural Networks (for time-series) and Natural Language Processing networks (for text).
Discover a new library called keras, which is a developer-friendly wrapper over tensorflow, a Deep Learning library created by Google. We'll teach you the fundamental techniques to build your first deep learning model with Keras.
Go further into computer vision with Deep Learning building networks for object detection and recognition. Implement advanced techniques like data augmentation to augment your training set by computing image perturbations (random crops, intensity changes etc) in order to improve your model's generalization.
Move from Jupyter Notebook to a code editor and learn how to setup a machine learning project in the right way in order to quickly and confidently iterate. Learn how to convert a machine learning model into a model with a robust and scalable pipeline with sklearn-pipeline using encoders and transformers.
Building a machine learning model from start to finish requires a lot of data preparation, experimentation, iteration and tuning. We'll teach you how to do your feature engineering and hyperparameter tuning in order to build the best model. For this, we will leverage a library called MLflow.
Finally, we'll show you how to deploy your code and model to production. Using Google Cloud AI Platform, you'll be able to train your model at scale, package it and make it available to the world. Cherry on top, you will use a Docker environment to deploy your own RESTful Flask API which could be plugged to any front-end interface.
You'll spend the last two weeks on a group project working on an exciting data science problem you want to solve! As a team, you'll learn how to collaborate efficiently on a real data science project through a common Python repository and the Git flow. You will use a mix of your own datasets (if you have any from your company / non-profit organisation) and open-data repositories (Government initiatives, Kaggle, etc.). It will be a great way to practise all the tools, techniques and methodologies covered in the Data Science Course and will make you realize how autonomous you have become.
From morning lectures to evening talks, every day is action-packed.
Grab a coffee and start every morning with an engaging & interactive lecture, before putting what you’ve learnt into practice.
Pair up with your buddy for the day, and work on a series of programming challenges with the help of our teaching staff.
Learning to code is very intense, so it’s important to take a break and relax during our yoga classes.
Review the day’s challenges and get an overview of upcoming lessons during live code sessions.
Be inspired and get priceless advice from successful entrepreneurs invited for exclusive talks.
Our Data Science course is just the beginning of the journey. Once you graduate, you belong to a global tech community and have access to our online platform to keep learning and growing.
Get tips and advice from professional data scientists & data analysts, access exclusive job and freelance opportunities from entrepreneurs & developers.
Access our online education platform at any time after the course: you will find all data science lectures, screencasts, challenges and flashcards.
Benefit from our global community of 8165 alumni working in data-related roles, but also entrepreneurs, developers and product managers all over the world.
Our different courses are running in 39 campuses all over the world: wherever you go, you belong to the Le Wagon community!
Once the course ends, you benefit from our career services. We help you meet with the best recruiters and connect with relevant alumni.
Access a complete guide to kick-start your Data Science career after the course: boost your portfolio, find your dream job, leverage on our 8165 alumni community.
Attend our job fairs and networking events, meet with the best tech companies and receive offers by recruiters looking for talent in data-related roles.
Our data science course alumni love to share their experiences with fresh graduates: they explain how they found their job as Data Scientist, Data Analyst or Data Engineer.
Our local teams know their alumni and hiring partners, what they are up to and what they are looking for. They introduce you to the right people depending on your goal.
The best companies partner with Le Wagon and hire our alumni as Data Scientist, Data Analyst or Data Engineer.
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Find out if you are eligible for special offers in Lisbon.
PUZZLE, BNI's Europa Credit brand, was born to expedite and revolutionize the way credit is granted in Portugal through a 100% online platform that aims to meet the needs of a new generation which it requires technology, speed, and flexibility.
Through PUZZLE, Portuguese nationals can receive financing on 90% of Le Wagon's bootcamp tuition for both the part-time and full-time programs.
Set up a call with our team to find out the next steps.
⚠️Eligibility: Resident in Portugal (>6 months)
We offer each scholarship recipient a €2000 discount on the total cost of Le Wagon’s tuition. We believe in making technology more open and available in order to foster creativity and develop the skills that will in turn further Portugal’s ecosystem.
Scholarships are only offered to applicants that are residents in Portugal for a minimum of 6 months. To be eligible, applicants must successfully complete Le Wagon's standard admissions process and be officially accepted.
⚠️Eligibility: • Resident in Portugal (>2 years) • Age 19 to 23 years old at the time of bootcamp
In an effort to increase the number of women in technology-related fields, we’re committing to help self-identifying young women pursue their dreams of becoming tech entrepreneurs, junior developers, and project managers.
Recipients of the scholarship cannot combine the scholarship with any other tuition reduction. All self-identifying women between the ages of 19 to 23 years old are applicable for the 50% reduction in tuition.
Le Wagon Alumni receive a 20% discount on our Part-time and Full-time Data Science Bootcamp here in Lisbon.
Nova SBE undergraduate, masters and executive education alumni receive a 20% discount on our part-time Data Science Bootcamp @Nova SBE.
If you got here, it means that you have questions about Le Wagon: how to apply, who can join, what you’ll learn… Good! We have the answers.
A minimum math level of “Matemática A - 11º ano” [High School Junior Year] is required for the batch. We need you to be comfortable with Functions, their Derivatives & System of linear equations. To get up to speed, some preparation work is given to applicants before the bootcamp start: Calculus, Linear Algebra & Statistics.
Yes, a fair minimum. Our Data Science bootcamp is very intense and will jump into advanced topics from the very first week. Unlike our FullStack Web Development bootcamp where we spend 3 weeks learning Ruby from scratch, applicants for the Data Science bootcamp need some programming.
How much? You must be comfortable with data types & variables, conditions, loops, functions and the two data structures list & dict [named Array and Hash in Ruby]. If you know those topics in Ruby, JavaScript or some other language than Python, feel free to embark on those free Fundamentals & Intermediate courses before the bootcamp.
For Nova SBE students, we have also found that the Introduction to Programming undergraduate course can give a suitable enough foundation to count as a pre-requisite.
Next Lisbon data science course full-time coding bootcamp starts on Sep 28, 2020
