Full-time (9 weeks)

In 9 intensive weeks in Singapore, learn Data Science from Python to advanced Machine Learning, get all the skills to join a Data Science team and boost your career.

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In 9 intensive weeks, learn Data Science from Python to advanced Machine Learning at Le Wagon.
Course details Apply now
Apr 19, 2021 - Jun 19, 2021 on campus Course in English (10,000 SGD)
Open - Apply now
Jul 5, 2021 - Sep 4, 2021 on campus Course in English (10,000 SGD)
Open - Apply now

Join a unique Data Science course

Our full-time Data Science in Singapore 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.

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 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.

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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.

Neural Networks

Unveil the magic behind Deep Learning by understanding the architecture of neural networks (neurons, layers, stacks) and their parameters (activations, losses, optimizers). Become autonomous to build your own networks, especially to work with images, times and text, while learning the techniques and tricks that make Deep Learning work.

Computer Vision

Go further into computer vision with Convolutional Neural Networks, architectures designed to take the most out of images. Improve your model generalization thanks to data augmentation techniques and implement advanced methods to benefit from state-of-the-art architectures thanks to Transfer learning methods.

Times-Series & Text data

Get comfortable into managing sequential data and text (sequence of words) by transforming them into appropriate inputs. Leverage the power of Recurrent Neural Networks to forecast future values and perform valuable Natural Language Processing.

Deep Learning made easy

Discover the Keras Deep Learning library which enables to prototype easily while having the flexibility to tune precisely your neural network. Moreover, Google Colab will greatly speed up the computational time thanks to dedicated GPUs.

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.

A typical day at Le Wagon Singapore

From morning lectures to evening talks, every day is action-packed.

  • 09:00 Lectures
  • 10:30 Challenges
  • 16:00 Yoga
  • 17:00 Recap
  • 18:00 Events 20:00
Lectures
Lectures09:00 - 10:30

Grab a coffee and start every morning with an engaging & interactive lecture, before putting what you’ve learnt into practice.

Challenges
Challenges10:30 - 16:00

Pair up with your buddy for the day, and work on a series of programming challenges with the help of our teaching staff.

Yoga
Yoga16:00 - 17:00

Learning to code is very intense, so it’s important to take a break and relax during our yoga classes, which run at least once a week.

Live code
Recap17:00 - 18:00

Review the day’s challenges and get an overview of upcoming lessons during live code sessions.

Talks & Workshops
Events18:00 - 20:00

Be inspired and get priceless advice from successful entrepreneurs invited for exclusive talks.

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.

Solomon Soh
Solomon Soh

Solomon joined our team as a lead instructor teaching Data Science part-time classes.

more about Solomon
Han Qi
Han Qi

Han joined our team as a lead instructor teaching Data Science part-time classes.

more about Han

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 10,636 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 43 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 business & tech companies in Singapore

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 10,636 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

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

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

Find the right financing option for you

Find out if you are eligible for special offers in Singapore.

TIPP (IMDA)

We've partnered with IMDA to provide up to 70% subsidies to fund your education!

Final cost with full subsidy: SGD 3,000 (no GST)

More information

The most acclaimed Data Science Bootcamp and courses

Le Wagon is the #1 ranked coding bootcamp on Switchup Coursereport logo

Le Wagon has 1957 reviews with an average grade of 4.98/5 which makes it the most acclaimed coding bootcamp worldwide on Switchup according to student reviews! Whilst these reviews make us proud, above all they make us happy. Behind these reviews are hundreds of people around the world who have had a life-changing experience joining our program, that has opened new doors for them. We feel blessed and honoured to have enabled them - and to keep enabling our students - to become autonomous in coding, upskill or change their career, or launch their own startups.

Also, these 1957 reviews are extremely important for us to make sure we’re always meeting the same level of excellence. Having such positive and enthusiastic reviews about our bootcamps is the ultimate proof that we provide the best tech education for all our students, in the 43 cities we run our coding bootcamps in.

Any questions about our program in Singapore

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 is the application process like?
  1. Fill in registration form (it's free and non-binding)
  2. Introduction call
  3. Self assessment track
  4. Confirmation of acceptance
  5. Contract signature + Invoice
  6. Le Wagon prep-course (± 40 hours)
What are the acceptance criteria?

Pre-requisite skills in programming and basic concepts of mathematics (pre-university level) are required. You need to be 100% motivated and committed. If you want to work in the tech industry or run your own company it's usually a good start. With a self-assessment course we make sure the bootcamp pace is right for you. Last but not least, your personality and outcome expectations need to be a good fit.

Minimum entry age is 18 and you need to be fluent in English. We don't require you to have working experience.

Is there any career support?

We have both internal and external processes to help you kick-start your career in tech.

  • Post Bootcamp capstone program
  • Review of your CV and cover letter.
  • Send your profile to our hiring partners.
  • Online tools hosted on our learning platform, including tech-test hands-on training.
  • Alumni discussion panels to share their experience and give you tips on your future career plans.
  • Dedicated job board on Slack only accessible to our global alumni community where we share all relevant job offers.
Do we get a certificate?

Yes, you will receive a certificate upon successful graduation of the course.

We are an accredited Private Education Institution (PEI) and our courses are registered with the Committee of Private Education (CPE) in Singapore.

Certificate criteria:
- Minimum attendance of 85%
- Daily completion of at least 1 core exercise
- Daily code contribution during project weeks

Are there any scholarships available?

We've partnered with IMDA to provide up to 70% subsidies to fund your education!

Final cost with TIPP subsidy: SGD 3,000 (no GST)

For more information, please click here

What are the assessment and examination like?

Students will perform regular quizzes to reinforce and monitor the learnt concepts. After correction of the quiz teachers discuss the results to identify if the student is on track or may need additional support.

Rather than a final exam the aim of the bootcamp is to produce a functional MVP of a meaningful product idea within a team. The teacher works with each group at every step of the user journey as well as hold daily stand up meetings to review progress and to-do tasks. Regular rehearsals are also held to ensure the product presentation is satisfactory to pitch to a live audience as one would in an entrepreneurial environment on the final Demo Day of the bootcamp.

For more questions & answers, you can visit our FAQ section! If you would like to discuss with Le Wagon team, don't hesitate to contact us.

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Want to go further?

Next Singapore Data Science course (full-time coding bootcamp) starts on Apr 19, 2021

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