Data Science course in Tokyo

Part-time (24 weeks)

In 24 intensive weeks in Tokyo, learn Data Science from Python to advanced Machine Learning, get all the skills to join a Data Science team and boost your career.

Apply now
 In 24 weeks, part-time, learn Data Science from Python to advanced Machine Learning at Le Wagon Tokyo
Course details Apply now

Some of our upcoming courses in Tokyo can be followed remotely. After you complete your application, the admission manager will be in touch shortly to give you all the necessary information.

Join a unique course

Our part-time Data Science in Tokyo course gives you the skills you need to launch your career in a data science team, in 24 weeks studying some weekday evenings and Saturdays. 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.

Le Wagon's Data Science course gives you the data science skills you need to launch your career in any data-related role.
Learn Data Science in 9 weeks
Check out what our alumni have built in 2 weeks

Our Data Science course curriculum

Our Data Science course is designed to make you learn step by step, from the basic data toolkit in Python to implementing Machine Learning model in a production environment.

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Start the bootcamp prepared!

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.

Python for Data Science

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.

Relational Database & SQL

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.

Data Visualization

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.

Statistics, Probability, Linear Algebra

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.

c pulse Statistical inferences

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

speaker Communication

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.

Preprocessing and Supervised Learning

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).

Generalization and Overfitting

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.

Performance Metrics

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).

Unsupervised Learning & Advanced Methods

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.

Managing Images and Text data

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).

Neural Networks

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).

Deep Learning with Keras

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.

Computer Vision

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.

Machine Learning Pipeline

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.

Machine Learning workflow with MLflow

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.

Deploying to production with Google Cloud Platform

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.

Student Projects

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.

Our part-time format

Learn to code in 24 weeks with a tailor-made program adapted to your busy schedule.

10:00 AM 05:00 PM
07:00 PM 10:00 PM
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
Homework Watch the lecture to prepare for next session.
On campus Pair program with your classmates on coding challenges with the help of our teachers.
On campus Pair program with your classmates on coding challenges with the help of our teachers.
Homework Watch the lecture to prepare for next session.
On campus Practice all day on challenges and projects.

Consolidate what you've learnt through live-code sessions with your teachers.
☀️
🏠Homework

Watch the lecture to prepare for next session.

🏫On campus

Pair program with your classmates on coding challenges with the help of our teachers.

A taste of our program in Tokyo

Live a unique learning experience every week.

On campus pair-programming sessions
On campus pair-programming sessions

Meet your peers and teachers three times a week to work on coding challenges. Learn to think and solve problems like a software developer.

Online lectures and flashcards
Online lectures and flashcards

Watch lectures at your own pace on our online platform. Grasp core concepts and prepare yourself for the next coding session. Consolidate your knowledge on a daily basis playing our Flashcards.

Hiring and networking Events
Hiring and networking Events

Every week, join us for events with entrepreneurs and hiring partners. Create your own network within a thriving tech scene.

Passionate teachers

Since day one, we’ve taken teaching seriously. Great teachers inspire us to connect to topics on a profound level. Experience as a developer alone doesn’t necessarily make one an effective teacher — that’s why we’re passionate about finding not only great engineers, but deeply committed, experienced teachers.

Sébastien Béal
Sébastien Béal

Graduated from École Normale Paris in Machine Learning and Computer Vision, Sébastien is the Founder and CEO / CTO of Locarise, a Tokyo-based IoT and spatial data startup aiming to make retail, offices, and event venues safer and smarter.

more about Sébastien
Fabian Dubois
Fabian Dubois

Graduated with a Computer Science degree from a top French engineering school, Fabian is currently working as a freelancer in Tokyo, leveraging on AI and Machine Learning to develop sustainable projects on earth and in space.

more about Fabian
Yann Le Guilly
Yann Le Guilly

Graduated with a Master's degree in computational science, Yann is currently working as Machine Learning engineer at Arithmer, a Tokyo-based AI startup.

more about Yann
Trouni Tiet
Trouni Tiet

Graduated from a top French engineering school, Trouni leads our Data Science bootcamp and teaches foundational courses in Python and Mathematics. He is also working as a freelancer and launching his own IT company in Tokyo.

more about Trouni

Network and learning platform

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.

Slack icon Slack groups

Get tips and advice from professional data scientists & data analysts, access exclusive job and freelance opportunities from entrepreneurs & developers.

Online classroom

Access our online education platform at any time after the course: you will find all data science lectures, screencasts, challenges and flashcards.

Tech community

Benefit from our global community of 9280 alumni working in data-related roles, but also entrepreneurs, developers and product managers all over the world.

Icon tutorials Global presence

Our different courses are running in 39 campuses all over the world: wherever you go, you belong to the Le Wagon community!

Community and tools for life

Find a data job in the best tech companies in Tokyo

Once the course ends, you benefit from our career services. We help you meet with the best recruiters and connect with relevant alumni.

microsoftwordCreated with Sketch. Career Playbook

Access a complete guide to kick-start your Data Science career after the course: boost your portfolio, find your dream job, leverage on our 9280 alumni community.

myspaceCreated with Sketch. Career Events

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.

buymeacoffeeCreated with Sketch. Alumni Coaching Sessions

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.

wechatCreated with Sketch. Career Intros

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.

Our web development course alumni get hired by the best companies

Where our alumni work in data in Tokyo

The best companies partner with Le Wagon and hire our alumni as Data Scientist, Data Analyst or Data Engineer.

Frichti Hired 1 graduates
Doctolib Hired 9 graduates
+7
Google Hired 5 graduates
+3
Getaround Hired 6 graduates
+4
Aircall Hired 3 graduates
+1
ContentSquare Hired 1 graduates

Any questions about our program in Tokyo

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.

What to expect from the enrollment interview?

The interview usually lasts one hour. We conduct it in two 30-min parts, first one focusing on your background and motivation, and second more "formal" one about maths and programming:
Maths questions are senior high school level maximum (e.g. derivatives, mean, simple statistical concepts)
Programming questions are here to check your understanding of basic programming concepts (e.g. variable, data types, simple algos)

The best way to prepare for this interview is to go through our prep work. There is no failing! If we think you need to study further, we will let you know which parts to improve, and you can apply for our next session.

What type of visa do I need to attend Le Wagon in Japan?

If you’re attending our 9-week full-time program, you only need to make sure you are eligible for a 90-day tourist visa. If your country is not in the list of eligible nationalities, we can provide supporting documents to apply for a short-term stay visa at your local Japanese embassy.

If you’re attending our 24-week part-time program, it’s important to check if you are authorized to stay in the territory for all program’s length.

Do I need to speak Japanese to join the bootcamp or find a job in Tokyo?

You do not need to be able to speak Japanese to join our program: all our curriculum, teaching platform, content and events are in English.

While speaking Japanese opens up opportunities when looking for a job, there are more and more companies in Tokyo ready to hire non-Japanese speakers. That said, JLPT N4 or N3 will be a proof that you are committed to living in Japan, and greatly helps communication within most companies.

What is the estimated cost of living in Tokyo?

Tokyo always had a reputation for being an expensive city to live in. The good news is, this is just a reputation. You can refer to this article for an estimated accommodation, food and transportation budget.

Can I pay the tuition in installments?

Our standard payment plan is as follows:
- Deposit upon contract signature (⅓ of the total tuition)
- Remaining balance due during the first month of the bootcamp

We do offer a payment option in three installments without extra fees for specific cases, upon request.
Please note that your spot will only be secured once we have received your deposit.

You can find additional details regarding payment options by following this link.

Want to go further?

Next Tokyo data science course part-time coding bootcamp starts on Feb 20, 2021