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Data Science

Jumpstart your data science training with this exciting

Demand for data analysts and data scientists is skyrocketing – in fact, the U.S. Bureau of Labor Statistics reports that 11.5 million new data job openings will be available by 2026. The Logical Operations certification path prepares students with the skills required for these in-demand jobs. Each course and certification builds upon the previous and offers the student the opportunity to move beyond data analyst and into data scientist.

Jumpstart your data science training with this exciting certification path from Logical Operations!

This course provides students with a foundation for Excel knowledge and skills, including performing calculations and modifying a worksheet.

This course builds upon the foundational knowledge presented in the Excel: Part 1 and will enable you to create advanced workbooks and worksheets to help deepen your understanding of organizational intelligence.

This course will enable students to perform robust and advanced data and statistical analysis using Pivot Tables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data, and visualize data and insights using advanced visualizations in charts and dashboards.

Students will build foundational knowledge with Tableau, including how to identify and configure basic functions of Tableau, connect to data sources, import data into Tableau, save Tableau files, and much more.

Students will learn how to perform advanced data visualization and data blending with Tableau, such as how to blend data to visualize relationships, join data, and access data in PDFs, and more.

Students will explore and learn how to visualize data with Power BI, including how to analyze data with self-service BI, connect to data sources, and perform advanced data modeling and shaping.

In this course, students will learn the fundamentals of programming in Python and be able to develop applications to demonstrate their grasp of the language.

Students will build upon their basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, threading, unit testing, and creating and installing packages and executable applications.

Students will learn how Jupyter Notebooks can be used with Python for various data-science applications. This fast-paced practical single-day course focuses on solving challenges presented by data science in a manner that is simple to conceptualize and easy to implement.

Students will learn how to use tools that can control an avalanche of data. They’ll learn effective techniques to aggregate data into useful dimensions for analysis, statistical measurements, and to transform datasets into features for other systems.

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