Our Python for Data Science Bootcamp is meant to go from the very basics of Python programming to the start of machine learning with Python.
Unlock the power of Python for data-driven decision-making as you master Python programming fundamentals and dive into data analysis. Acquire essential skills to explore and manipulate data, create insightful visualizations, and perform statistical analysis, all through hands-on projects with real-world datasets.
Our Python for Data Science Bootcamp is meant to go from the very basics of Python programming to the start of machine learning with Python. In this bootcamp, you’ll learn how and why Python is used for data science, how to create programs, work with data in Python, create data visualizations, and use statistics to create machine learning models.
The course will start with the fundamentals of Python, including writing basic statements and expressions, creating variables, understanding different data types, working with lists, indexing and slicing lists, using functions and methods, and more. Concepts such as object-oriented programming are introduced.
Once a learning environment has been set up, we will work with different data types such as strings, lists, dictionaries, and tuples. Each data type has its own particular purpose, and knowing when to use each one will be essential.
The second part of the course covers conditional statements and control flow tools. This includes the If/Else statements, boolean operations, and different types of loops.
These topics create a large portion of the logic in your code, and this course will help you master these concepts. Learn to work with dictionaries, create functions, write for loops to iterate through data, and work with packages in Python.
The third part of the course introduces operations and tools for data science. We will learn how to import and clean data using NumPy and Pandas. You’ll learn to work with Pandas dataframes, wrangle data, and get descriptive statistics for your data.
You’ll learn to analyze and visualize data with key data science libraries, including Pandas, NumPy, and Matplotlib. Learn to filter and clean data, group and pivot data, and start generating insights from your data with exploratory data analysis. Then create visualizations, including bar charts, histograms, and advanced visualizations, for easy interpretation and sharing of your data insights.
After learning all the foundational Python programming and data analysis skills in this bootcamp, you will be ready to dive fully into machine learning.
Our Python Machine Learning Bootcamp builds off this foundational knowledge to turn you into a full-time machine learning data scientist. Pick up right where the Python for Data Science Bootcamp left off with advanced statistics and create machine learning models with logistic regressions, k-nearest neighbors, and decision trees.
Meet the global demand for technical problem-solvers by developing your coding skills to create full-stack web applications across multiple frameworks, incorporating functionality from third-party APIs, executing software engineering projects in an Agile development workflow, and more.
If you are interested in an in-person coding class in Toronto, you’ll find plenty of options to choose from. Schools offering face-to-face training sessions locally include General Assembly, New Horizons, Data Science DoJo, and BrainStation.
General Assembly offers a beginner-friendly Python Course. Students learn coding in Python through a hands-on approach by building programs and working with data. The course covers object-oriented programming and data science fundamentals.
Another class offered by General Assembly is a 10-week Data Science Course. This class is for students with a background in programming or a quantitative field. The class centers around Python programming and data exploration, data modeling, and machine learning.
General Assembly’s beginner-friendly Front End Web Development Course teaches students HTML and CSS to build and style a website and JavaScript to make a website interactive.
BrainStation’s Data Science Program teaches data analysis, modeling, and programming in Python. Using Synapse, students learn how to clean and analyze data, create visualizations, and use Python components such as Pandas and NumPy.
BrainStation also offers a Python Programming Certificate. Students start by learning syntax, data types, and operations, then move on to more advanced data types and the fundamentals of algorithms.
You can attend in-person SQL and Python classes at New Horizons. SQL Fundamentals Part One, offered by New Horizons, teaches students how to execute a simple query, use various functions to perform calculations on data, organize the data obtained from a query before it is displayed on the screen, retrieve data from multiple tables, and export the results.
In SQL Fundamentals Part Two, students use subqueries to generate query output, manipulate data, create indexes on table columns, and drop inefficient indexes. In the Using Data Science Tools in Python course, students learn about Python’s robust libraries and how to use them for analyzing and making visualizations from data.
This course sits in the "additional courses" block of the New Science Program. It introduces science students to computer programming with the most widely used object-oriented programming language, C++.
This Java programming training includes the use of objects, strings, arrays, loops and Predicate Lambda expression. The Java programming course imparts core skills to develop rich applications using JDK 8 Technology and the NetBeans IDE.
Manufacturing in Canada is increasingly automated, requiring workers who are up to date in digital technical skills. Computer Numerically Controlled (CNC) machine tools are used to manufacture a variety of parts and products across numerous industries to increase accuracy and precision, and elimina...
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This course is designed to prepare students for the American Computer Science League (ACSL), the USA Computing Olympiad (USACO) and the Canadian Computing Competition (CCC). Pre-requisites: a solid background in coding (completion of Java Level 2 or AP Computer Science A).
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