Data Classes Ottawa

Fifty hours of training in the essentials of data science and data analytics prepare graduates for a career change or advancement in this training. Topics include data visualization, SQL, statistics and Python, A/B testing and web analytics, and machine learning.

Instruction in the essential elements needed when working with big data is the focus of this course. Students learn about data visualization, SQL, Python with statistics, A/B testing, and machine learning in this program.

Students in this program learn Python programming, database management with SQL and MongoDB, machine learning, data visualization, how to work with Big Data using Hadoop and Hive, deployment with Docker and Kubernetes, and more.

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.

This course covers the skills needed to become a Data Analyst or Business Analyst, including data analytics fundamentals, visualization with Tableau, using Python to clean and manipulate data, and how to work with relational databases. One-on-one mentoring is included.

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 1-day Excel course was designed to teach beginners the basics of working with spreadsheets. The course covers a range of beginner Excel concepts and tools, including an introduction to the Excel environment, formatting a spreadsheet and the data it contains, basic functions and formulas, and how to save and print Excel documents.

This 2-day Excel course was designed to teach beginners more than just basics of working with spreadsheets. The course covers a range of beginner and intermediate Excel concepts and tools, including how to customize Excel, functions and formulas, sorting and filtering, how to protect files and spreadsheets, creating charts, working with external data sources, validating data, conditional formatting, and more.

This 2-day advanced Excel course was designed to teach regular spreadsheet users some of the more advanced functions available within Excel. The course covers a range of advanced Excel concepts, including what if analysis, how to consolidate data, advanced functions, a variety of advanced Excel tricks, an introduction to macros, and best practices for working with pivot tables.

This 2-day advanced Excel course was designed to teach regular spreadsheet users some of the more advanced formulas and functions available in Excel. The course covers a range of advanced Excel formulas and functions, including a review of formula basics, using logical, reference, and statistical functions, as well as various math, finance, and error checking functions.