A data project using Deep Learning to recognize waste on camera and classify if it can be recycled, composted, or trashed.
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Our Data Science course in Montreal takes you from Data Enthusiast to Data Scientist in 9 weeks. You will be able to analyse data to make decisions, implement AI and Machine Learning models and build a practical data application ready for real-world deployment. Enter the world of Data Science as a Data Analyst, Data Engineer or Data Scientist, enhance your academic studies, solve global issues, or advance your career with our 600+ global hiring partners in industries such as marketing, finance, and commerce with a unique data skillset.
Our course in Montreal is designed to help you learn Data Science step by step. Use data to provide actionable insights and build a real-world data application to showcase your skills.
Learn programming in Python, how to work with Jupyter Notebook and to use powerful Python libraries like Pandas and NumPy to explore and analyse 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 visualisations 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.
In Montreal you will learn about 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 vectorisation. 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.
Unveil the magic behind Deep Learning by understanding the architecture of neural networks (neurons, layers, stacks) and their parameters (activations, losses, optimisers). 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.
Go further into computer vision with Convolutional Neural Networks, architectures designed to make the most out of images. Improve your model generalisation thanks to data augmentation techniques and implement advanced methods to benefit from state-of-the-art architectures thanks to Transfer Learning methods.
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.
Move from Jupyter Notebook to a code editor and learn how to set up 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 into any front-end interface.
The final weeks of the course will culminate in the delivery of your capstone project! Working collaboratively in small teams, the project will allow you to utilise all the skills you have learned throughout the bootcamp in order to solve a real world data science problem.
After trying to learn on my own, I enrolled at Le Wagon. It was an amazing decision. The program is fast-paced but so exciting! The curriculum is built such as you are never lost. The staff is always there to help you when you get stuck!
Most of your day is spent practicing and the TA's are available to guide and support you. It's not an easy course and you learn a lot in a short period, but the support you get and the structure of the course makes sure that you are able to continue
Our Data Science course requires a basic level of Python & Mathematics. As we want all of our students to succeed, you'll be able to test your level and refresh your skills before the Bootcamp starts.
You'll need to be comfortable with data types & variables, conditions, loops, functions and data structures (List & Dictionary).
You'll need a High School level of Maths, meaning you will be comfortable with functions, derivatives, and systems of linear equations.
After a chat with our Admissions team, you will receive a Python & Mathematics Quiz to help you and the Admissions team better understand your current level in Python & Maths. We'll also provide you with a set of additional free learning resources to help you match the prerequisite level for the Bootcamp.
Once you have been accepted onto the Data Science Bootcamp (congrats!), you'll receive ~ 40h of online learning resources. We require all of our students to complete this before the Bootcamp starts, either at their own pace or during our Data Prep Week.
The Data Prep Week takes place the week before the official start date of the Bootcamp. This is an additional week of interactive online learning designed to help you get through this content as efficiently as possible and ensure you have the necessary foundations in Python before the bootcamp starts.
From morning lectures to evening talks, every day in Montreal 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 can be very intense. If you want, you can make the most of the yoga classes we organize on certain days to relax and take a break.
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.
At the end of the bootcamp, we will organise our Career Week. This week gives you the tools you need to take the next steps in your career, whether it is finding your first job in a Data Science role, exploring career opportunities with your new data skill set, or launching your start-up.
Benefit from a combination of panel discussions, workshops, presentations, and assignments to help you find the right career path.
Prepare your personal profile, complete job applications, prepare for technical challenges, and make a game plan for after the bootcamp!
Hear from alumni about their post-Bootcamp journeys and what a typical day looks like in their new careers.
You can join any workshops or watch any tutorials that you are interested in. You create your own career week according to your interests and objectives
The last weeks of our Data Science course in Montreal will culminate in the delivery of a fully deployable data application. Working collaboratively in small teams, the data project will allow you to utilise all the skills you have learned throughout the bootcamp in order to solve a real-world data science problem.
A data project using Deep Learning to recognize waste on camera and classify if it can be recycled, composted, or trashed.
Using a Tensorflow Model and different posture images, the app analyses and categorises your image and suggests the right exercises to correct your posture from an API.
Market Prediction is a machine learning model that gives insights about stocks to help investors make informed decisions.
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.
Renan is a data aficionado because he believes data tells true stories no one else could. As Vice President of Data Science & Engineering Lead at JPMorgan, he’s been taming chaos with AI and millions of data points every day.more about Renan
After studying Energy Economics, Vinny became interested in data science and AI. He attended Le Wagon's web development bootcamp and worked as a full stack developer before coming back to Le Wagon for the data science bootcamp and becoming a teacher.more about Vinicius
Guillaume is Belgian and currently based in Bamako. He transitioned to Data Science in 2020 after 7 years of working as a Finance project manager. He has a Master in Environmental Management and is mainly interested in geospatial and climate data.more about Guillaume
After 15 years of experience in management and support, Samuel transitioned to the data industry last year thanks to Le Wagon's Bootcamp. He is now a Data Analyst at Ludia and works with SQL on a daily basis.more about Samuel
Georges is Applied Machine Learning Scientist at Microsoft. After completing a Bachelor in Applied Mathematics, he specialized in Deep Learning and NLP. He has experience working in Education Technology and Business Consulting.more about Georges
As a domain expert at the intersection of AI and medicine, Houda is passionate about developing machine learning products for accessible healthcare. She's also involved in community initiatives to promote women in tech and digital literacy.more about Houda
After teaching English and graduating in chemical engineering, Amanda decided to change careers. She finished an MBA in Economical Engineering, learned to code & enrolled in the Data Science program. She's now a Junior Data Scientist and a teacher.more about Amanda
A Data Scientist working at Local Logic, Guy holds a Bachelor of Science and a Master in Biomedical Engineering from Ben Gurion University & McGill University respectively, where his focus was signal processing & object tracking in video recordings.more about Guy
Lucas is a battle-tested data nerd with over 10 years of practical experience in Data Science, acquired solving real-life problems using data at large companies such as Dell and National Bank of Canada, as well as his own business ventures.more about Lucas
Head of Research at Dataperformers Inc, Viral has a background in academics, research & applied engineering. A PhD candidate, he is working towards development and improvement of core AI and machine learning algorithms for computer vision.more about Viral
The team of teachers, TA's and the staff at Le Wagon were always there when we had questions. You can sense that they are very passionate about what they do and giving us all the tools we need to succeed.
Montreal's 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 14,932 alumni working in data-related roles, but also entrepreneurs, developers and product managers all over the world.
Our different courses are running in 41 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 in Montreal and connect with relevant alumni.
Access a complete guide to kick-start your Data Science career in Montreal after the course: boost your portfolio, find your dream job, leverage on our 14,932 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 more recent graduates. They explain how Le Wagon helped them find their dream role in Data Science and share insights into how they used their new data skill sets to accelerate their careers in various sectors, such as marketing, finance, healthcare and academic research.
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 Scientists, Data Analysts, Product Managers or Data Engineers.
Le Wagon has 2271 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, which 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 2271 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 41 cities we run our coding bootcamps in.
Data Science course in Montreal
Le Wagon Montréal Coding Bootcamp
5333, avenue Casgrain, suite 102, Montréal (Québec), H2T1X3
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.
Check our financing options to find out more about the current scholarships available.
We have a partnership with a financial institution (Caisse Desjardins des TI), that offers low-interest student loans and flexible payment options. This option is available for all students who are approved in the first steps of our selection process and are Canadian citizens or residents.
Further Readings: The reasons why to use RRSP to go back to school.
If you’ll be attending the 9-week full-time bootcamp, simply entering Canada as a visitor with a valid passport is usually enough. That said, some people may require a visa or an Electronic Travel Authorization. While we don’t formally assist students with acquiring visas, we’re happy to point you in the right direction. Here’s some useful information to help find the travel documents you need.
If you’re planning on attending the 24-week part-time program, make sure to check (and double check!) whether you’re authorized to stay in Canada for the program’s entirety.
The cost of living might vary a lot according to your lifestyle. You can find here more information about the neighbourhood we are located at and also some links with apartments for rent - some of them are suggestions from our alumni.
Yes :-) We do support all our graduates in finding the right career path after the bootcamp, sharing them all the necessary resources to build the best LinkedIn profile, getting the best out of the alumni Slack channels, enjoy our exclusive perks, get prepared for technical interviews, land their first job as developers, product managers or in a data team, launch their startup or start their freelancing career.
We organize career weeks after each bootcamp that include inspiring talks, practical workshops, coaching session, and networking events with alumni. We also organize job fairs or networking events with recruiters every season (four times a year). See one of our career week' s video
However, we consider that the ability of each graduate to find a position after the bootcamp is highly based on the student's motivation and work. Guaranteeing 100% employment at the end of the bootcamp would be dishonest in that regard. When choosing a bootcamp, what you should focus on is the quality of the curriculum and teachers. You should ask yourself about the skills you will have at the end and the product you will be able to build. This is what will really make you hireable.
Keep in mind that Le Wagon has an excellent network within the tech industry and a very good reputation with recruiters. Our students massively benefit from this. Moreover, we now have thousands of alumni worldwide. This internal network is your first support when looking for a job: our alumni work for the best tech companies out there and can recommend you for a position, and they'll also be available to support you during the search - by answering technical or non-technical questions.
We have hundreds of alumni who graduated from one of our batches in Montréal, most of them living in the city. After Le Wagon, the majority found a new job (either as a product manager or developer). A part of them are working as freelancers now and around 10% of them are entrepreneurs. It’s a rich, diverse and vibrant community!
If you already have a work permit and are authorized to work in Canada, it will make the job search process faster. If it is not the case yet, find more information about different types of work visas. You could also check eligibility to immigration programs, such as Express Entry or Quebec Immigration Programs.
But again, as we mentioned before, to attend the full-time bootcamp you only need to enter to Canada as a visitor :)
Your tuition is tax deductible. We'll issue a T2202A for you to claim your tuition for the program on your tax return. For student living in Québec, we will also issue a receipt for your tax filing at Revenu Québec.
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.
Next Montreal Data Science course (full-time coding bootcamp) starts on Jul 4, 2022