Data scientists collaborate closely with business stakeholders to identify data-related strategies to achieve their goals. They construct algorithms and prediction models to extract the data the organization requires.
Furthermore, data scientists design data modelling processes, assist in data analysis, and collaborate with others to share insights.
The data scientist curriculum offers in-depth instruction in data science and machine learning along with practical experience using important tools and technologies, such as Python, Tableau, and machine learning ideas. The final project for this course will prepare you for employment by giving you practical experience that can be applied to real-world challenges.
Data professionals are in great demand; according to the job bank of Canada, Over the years 2019 to 2028, a countrywide labor shortage is anticipated for this occupational category.
Get trained by industry Experts
Our curriculum is kept up to date with the latest industry trends ensuring all our graduates are prepared for the job market.Project Based Learning
Our courses are delivered by professionals with years of experience having learned first-hand the best, in-demand techniques, concepts, and latest Business Analyst tools.Learn while you Work
Our students have access to their labs and course materials at any hour of the day to maximize their learning potential and guarantee success.State of the Art Infrastructure
Graduates from MCIT have access to a complete work-oriented program that gives them access to CV/resume preparation, the latest job opportunities within their desired fields, provided continuously via24/7 Lab access
Working closely with our industry expert instructors, they can provide guidance and help you network within the field, providing you with a unique advantage in the workforce.Data Science Bootcamp
Download OutlineLearn the definition, process, and possible applications of Data Science.
Introduction to the concepts of programming and algorithms. Students will learn the Scala programming language, object-oriented languages such as Java and Linux Shell, as well as scripting fundamentals
In this course you will learn how to use SQL to store, query, and manipulate data. SQL is a special-purpose programming language designed to manage data in a relational database and is used by many apps and organizations across the globe.
This course aids in your mastery of Tableau Desktop -a widely used corporate intelligence, reporting, and data visualization tool. With the help of our Tableau training, you may advance your analytics profession and acquire employable skills.
Employers value Tableau skills highly for data-related positions, and our course teaches you how to utilize the tool efficiently for data preparation, interactive dashboard creation, the addition of different dimensions, and in-depth analysis of outliers.
The mathematical underpinnings of machine learning are given at the start of this course. Before moving on to multivariate and logistic regression, it begins with a review of linear algebra and univariate linear regression.
Furthermore, it switches topics every week to cover a wide range of machine learning models and approaches. Deep learning, support-vector machines, and principal component analysis are a few of these.
Finally, it discusses relevant practical issues like how to plan and use significant machine learning initiatives.
You'll have a thorough understanding of machine learning, its ideas, and its methodologies at the end of the course. In addition, you'll be able to use core machine learning algorithms like k-means clustering and back propagation.
Having advanced skills in Python is crucial for many data science roles. In this course, you will continue to build on the Python programming skills you acquired in the previous class by applying them to analytical projects.
You will learn Python for data science together with concepts such as data wrangling, mathematical computing, and more using a blended learning approach. Data Science with Python training can help you advance your career as a data scientist.
In the last stage of your data science training, the newly acquired skills will be put into practice through a real-world project.
The student will learn how to tackle a practical, industry-relevant problem by focusing on mentorship sessions for data processing and model creation. The project will provide you an opportunity to practice it in a practical setting.
Have a High School Diploma or equivalent.
Complete an interview with a member of our Admissions Team.
Commit to program and job search requirements.
Developer, Morgan Stanley
Data Analyst, Lamour
Data Engineer, Next Pathway Inc.
Big Data Developer
Upon successful completion of the program, students will receive a MCIT Bootcamp certificate in
Data Science
Our financial partners offer loans and personalized support to local entrepreneurs and internationally trained professionals.
The Montreal College of Information Technology awards scholarships prospective students to make quality education more accessible.
I am an engineering graduate from Morocco who came to Canada in order to help expand my career. I came upon MCIT as the best choice for intensive and practical courses, which opened up my career to far more opportunities than I thought were possible.
Sihame Benhlima — BI StudentRegistration deadline:
For international students, it is highly recommended to register two months before the starting date. Talk to one of our advisors for more details about the registration process.