Courses

Data Analytics and Its Applications

Every discipline is becoming progressively more data driven. Although we now possess the ability to easily collect, store and analyze data, we are facing a shortage of data analysts in the workforce. This course is designed to be a crash course that will provide working professionals with intermediate and advanced skills in data analytics.

This course contains no sessions
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Data Visualization in Power BI

An introduction to data visualization, dashboarding and reporting techniques. Data visualization is an importantcomponent of data science and data-driven decision making.

This course contains no sessions
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Introduction to Data Science - Data Analytics

Thanks to continuous improvements in technology, every industry is becoming progressively more data driven. Data analytics is the science and art of analyzing data and using that information to make informed decisions.

This course contains no sessions
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Introduction to Data Science - Introduction to Data Organization and Preparation for Analysis

The world is full of data. However, before that data can be analyzed and insights can be gleaned from it, data must first be organized, integrated, cleaned and prepared for analysis. This course introduces the tools and techniquesthat students can use to format their data, leading to hassle free analyses

This course contains no sessions
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Introduction to Python

The ability to code in Python is one of the most highly sought skills in data scientists. This course is designed to provide students with a foundation in Python programming.

This course contains no sessions
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Introduction to R

The ability to code in the statistical programming language R is one of the most highly sought skills in data analysts and statisticians. This course is designed to provide students with a foundation in R programming.

This course contains no sessions
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Machine Learning and Predictive Modeling

In this age of "big data", machine learning and predictive modeling tools enable us to describe and analyze large and complex data that we could not begin to comprehend without the help of computers. This course introduces different machine learning and predictive modeling techniques, the strengths and limitations of each of these techniques, and how these techniques can be applied to real-world datasets.

This course contains no sessions
Click here to submit a question or be notified about the next scheduled program.