Learn the essential skills needed to become a Data Analyst or Business Analyst, including data analysis, data visualization, and statistical analysis. Gain practical experience through real-world projects and prepare for a successful career in the field of data analytics.
DurationLearn the essential skills needed to become a data analyst or business analyst, including data analysis, data visualization, and statistical analysis. Gain practical experience through real-world projects and prepare for a successful career in the field of data analytics.
Why Data Analysts Are Needed in Today’s Workforce
Data analytics is the process of extracting information from raw data and generating actionable insights. It’s one of the most sought-after skills in the IT (information technology) marketplace, with demand spanning multiple sectors such as healthcare, finance, retail, real estate, education, gaming, and more.
Data analytics is about using data to make future decisions. It’s used to help companies solve problems, such as reducing risk, improving operations, or detecting fraud. Data analytics also heavily emphasizes data visualization to communicate your findings to others.
Learn with Real-World Projects
This applied, project-based course prepares students to gather, wrangle, analyze, and visualize data using various tools and technologies to help businesses in decision-making and strategy. Students will also have the opportunity to work on multiple real-world projects to advance their careers in analytics.
In this training, you’ll explore both predictive and prescriptive analytics by looking at case studies:
Predictive analytics uses regression models or forecasting techniques to examine past data to predict future outcomes.
Prescriptive analytics help optimize decision-making with constraints with such tools as Scenario Manager and Solver.
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.
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