Data Science Classes Toronto

Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries.

Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries.

Create robust predictive models with statistics and Python programming. Build confidence and credibility to tackle complex machine learning problems on the job. This course is offered in person and live online, in a remote classroom setting.

This data science program uses project-based learning to teach students data analysis, modeling, and programming in Python. Using Synapse, a data-driven Learning Management System, students will learn how to clean and analyze data, create visualizations, and use the fundamental components of programming to work with Python, Pandas, and NumPy. Students can take advantage of online and on-campus options.

Harness Excel, SQL, and Tableau to drive powerful analysis and insights. Build confidence and credibility to apply this versatile skill set to countless jobs. This course is offered in person and live online, in a remote classroom setting.

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's Numpy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.

In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.

In this course, students expand their Python programming skills into machine learning and algorithms that can independently learn patterns and make decisions. The course begins with linear and logistic regressions, the most time-tested and reliable tools for approaching a machine learning problem. Students then progress to algorithms with a different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. Participants also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.

Data Science Flex is a 6-month part-time program that will prepare you to to be a data scientist. This program comes with a tuition back guarantee if you can't land a job within 6 months after your graduation. To be accepted into this program, you will have to complete 3 weeks of prepwork and pass an assessment test before you start. Once you're accepted, you'll learn how to clean data using Python, query data using SQL, learn how to train and evaluate supervised and unsupervised machine learning models, and choose a track to specialize. You can deepdive in natural language processing, big data and spark, and deep learning with TensorFlow and Keras.

This 2-day course provides a deep-dive into using Python for data analysis. Students will get comfortable with the basics of Python programming and start working with Numpy Arrays, pandas, and MATPLOTLIB to perform data analysis and create data visualizations. This intensive course is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.

This data science program is a beginner-friendly bootcamp designed for individuals interested in learning the best practice of working with data and understanding how to gain insights from large data sets. In this hands-on bootcamp, students will get an overview of data science, including the various roles within data science and how to recognize and solve problems with data science. Students will also discuss how to use some well-known statistical models and how models fit into a data science project. Finally, students will explore various tools, including data visualization, analytical, and modeling tools essential in the field of data science.

This Python and machine learning course is a 2-day bootcamp designed for individuals with some familiarity with Python programming looking to advance their skill set. In this hands-on bootcamp, students will learn how to use some Python data science libraries and various machine learning techniques. Day one of the bootcamp focuses on introducing students to two data science libraries (NumPy and Pandas), best practices for preparing data, an intro to machine learning, and regression analysis. Day two starts off with cross validation and regularization of data, concludes with classification, and brings everything learned in days one and two together.

This SQL bootcamp is a beginner-friendly workshop designed for individuals with no prior knowledge of SQL who are eager to learn. In this hands-on workshop, students will learn the basics of SQL syntax and how databases are organized. Students in this course will also learn how to query data, aggregate data with statistical functions (SUM, AVG, COUNT, etc.), group data, and use conditional operators (=, <, >, etc.) to sort and filter data, and much more. Students will also learn when and how to use UNIONs and JOINs to merge data to spot trends and other insights.

Beginners welcome in this introduction to data analytics course, learning subjects such as organizing and analyzing data with Google Sheets as well as making charts and visualizations. Students also learn how to write database queries with SQL, explore Tableau, and gain an introduction to Python for data analysis.

This 2-day course on Python with data science is intended for software developers, IT architects, and data scientists. This course will build on their knowledge of statistics and programming, teaching them the theoretical and technical aspects of the use for Python. Students will learn about the history and purpose of data science, life-cycle phases of data analytics, methods for repairing and normalizing data, and how to aggregate and group data. Students will also complete 10 lab exercises.

This course in data analytics serves as an introduction to data analysis. Professionals who take this course will obtain essential data analysis skills, including the use of Tableau for visualizations. This program offers online and on-campus versions, with instruction by experienced data analysts. Graduates are equipped to solve real-world data problems.

If you want to become a data scientist, you should enroll in this intensive twelve-week bootcamp. Participants learn how to extract data from multiple sources to empower decision-makers. Specific course topics include Python, GitHub, and other data foundations, matplotlib, Seaborn, and other data visualization tools, Flask, Docker, and other data engineering platforms, data wrangling with JSON, SQL, and XML, machine learning models, and deep learning techniques.

This course teaches the fundamentals of SQL querying. This 1-day program teaches students how to execute a simple query, perform a conditional search, work with functions, and organize data. Further, students will learn how to retrieve data from multiple sources and export query results via a text or XML file.

This 1-day course builds on the fundamentals of SQL querying. This intermediate program teaches advanced querying techniques. The coursework will cover the use of subqueries to perform advanced querying, manipulating table data and table structure. Students will learn how to work with views, index data and manage transactions.

This 3-day introductory course teaches the basics of SQL databases. Through the use of labs and lectures, students will learn the fundamentals of data modeling, the use of relational databases, and the normalization of raw data. Students will also learn how to design relationships, evaluate query performance, and use stored procedures.