Most companies aren’t yet leveraging the powerful insights hidden within their data, which is where data scientists come in. Harness the predictive power of data to work at the forefront of diverse industries to solve the world's most interesting problems.
Our classes are taught in a group setting, live online using zoom and led by an instructor. With our cohort based classes, you'll learn with the same group of students from beginning to end.
Joining our Bootcamp will immediately grow your network. You'll meet our instructors, alumni, and students who are all deeply interested or actively working in tech. Most importantly - they love to help each other out.
Our bootcamps are designed to help you launch a career in tech quickly. We focus on teaching you the essentials and helping you build projects to showcase to potential employers.
Our career team will teach you the must dos- and must not dos when it comes to your job search to help you get hired.
To keep our classes intimate we find the ideal size is less than 25. From our experience, this creates the perfect dynamic of collaboration and class energy.
As a bootcamp grad, you'll earn a diploma from The Centre for Continuing Education at Concordia University. As one of Canada's largest universities, your education will be recognized by employers across the country.
This introductory module seeks to get you comfortable with Python and teach you how to use it to solve complex math & stats problems. We'll also introduce libraries such as NumPy and Pandas.
This module is for you to learn the importance of visualizing data. Visualization is a central part of Data Science and Data Analysis. Whether it is presenting results to a group of investors or simply trying to understand the relationship between data points.
This module introduces you to algorithms, data structures, and OOP. This module helps you understand how to efficiently code functions and the importance of data structures in helping certain programs run faster.
This module introduces you to linear and logistic regression. Understanding how to predict continuous and discrete values. How to engineer new features and also how to use different types of linear regressors to help normalize data and also when faced with some exotic distribution. It also introduces core statistical concepts such as hypothesis testing and revisits probability. This is a core module that transitions you into the Machine Learning component of the course.
This section introduces you to Structured Query Language or SQL. You will learn how to perform simple queries and will have the opportunity to attempt some extremely difficult queries. You will be introduced to the map-reduce paradigm and also look at how to utilize PySpark to work with data on computer clusters (essentially data that is too large to fit on one computer).
This module introduces you to different ML concepts. Here you will start with looking at optimization and how the use of Gradient Descent is leveraged for our ML algorithms to find the optimal solutions. You will also explore the concept of clustering which comes from the Unsupervised Learning paradigm. Then, you will learn how to scrape data online as well as how to use API to access web data. Lastly you are introduced to the concept of dimensionality reduction as well as NLP or natural language processing.
This final module focuses on the more deep-learning aspects of the course. Now that you have a good foundation of ML, you are ready to look at more robust models as well as being introduced to Neural Networks. You are also introduced to TSA or time series analysis models. Which are quite complicated models that help us predict certain sequences which are time related.
The Data Science Bootcamp was created for people looking to launch careers in Data as quickly as possible. Over the past few years, we've proven that we're a great fit for most people who love to problem solve.
Click hereto learn more about our payment plans, financing options, discounts, and tax credits.
Apply NowWell, kind-of 🤔. We've seen sooo many students who were beginners excel in either of our programs, in fact this makes up the majority of our students. But these are still pretty tough courses 💪🏽 - so when you apply, you'll meet with one of our learning advisors to make sure this is the right fit for you.
To keep our classes intimate we find the ideal size is less than 25. From our experience, this creates the perfect dynamic of collaboration and class energy.
For a complete breakdown of payment options, check out this document.
Feeling like you have more questions than answers 🤔 - we feel you. Book a time with us here so we can chat.
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