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 learning path prepares students with the skills required for these in-demand jobs. Each course 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 learning path from Logical Operations!
|Microsoft Excel: Part 1 >
This course provides students with a foundation for Excel knowledge and skills, including performing calculations and modifying a worksheet.
|Microsoft Excel: Part 2 >
This course builds upon the foundational knowledge presented in 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.
This course will give students a good foundation for creating, and using VBA in their own Excel workbooks, show them how to work with data across different applications, and how to package and share the macros and functions they create.
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, access data in PDFs, and more.
Students will 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.
This course presents the basic concepts, models, and tools that all professionals who deal with data science in any business role will need to grasp.
In this course, students will learn the fundamentals of programming in Python 3 and will create a complete program that performs a wide range of operations on a variety of data types, structures, and objects.
Students will build on 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.
Python's robust libraries have given data scientists the ability to load, analyze, shape, clean, and visualize data in easy to use, yet powerful, ways. This course will give students the skills to successfully use these libraries to extract useful insights from data and uncover business value.
Certified Data Science Practitioner (CDSP) is a vendor-neutral, high-stakes certification designed for programmers, data professionals, and analysts seeking to validate their knowledge and skills in the area of Data Science.
|Big Data Visualization and Analysis
|Data Automation with AI
with Python* >
with Python* >
|SQL Querying >
|Data Science Projects
with Python* >
Certified Ethical Emerging
|Applied Data Science
with Python and Jupyter*>
|Big Data Analysis with Python*>
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