R and Visualisation Using Power BI Course Overview

To ensure that you have a successful learning experience in the R and Visualization Using Power BI course, the following minimum prerequisites are recommended:

• Basic understanding of data types and structures (such as integers, strings, arrays, etc.)
• Familiarity with basic statistical concepts (mean, median, mode, etc.)
• Experience with any programming language (helpful but not mandatory for understanding programming concepts)
• Elementary knowledge of Excel or any other spreadsheet software
• An analytical mindset and willingness to learn new data analysis tools
• Basic computer literacy and proficiency in using Windows or Mac operating systems

Please note that while prior experience in programming or data analysis can be beneficial, it is not strictly required. The course is designed to guide you through the fundamentals before progressing to more advanced topics.

Target Audience for R and Visualisation Using Power BI

1. Elevate your data expertise with R and Power BI, designed for professionals keen on data analytics and visualization.

   
   

2. Target Audience for "R and Visualisation Using Power BI" course:

   
   

• Data Analysts
• Business Analysts
• BI Developers
• Data Scientists
• Data Engineers
• Statisticians
• Research Scientists
• Academic Researchers
• Marketing Analysts
• Financial Analysts
• Business Intelligence Consultants
• IT Professionals with an interest in data analysis
• Professionals looking to enhance their data visualization skills
• Individuals aiming to learn about data analytics and business intelligence tools

Learning Objectives - What you will Learn in this R and Visualisation Using Power BI?

Introduction to Learning Outcomes and Concepts Covered:

This course equips students with the skills to harness the power of R for data analysis and to leverage Power BI for insightful data visualization.

Learning Objectives and Outcomes:

• Understand the basics of R programming including syntax, variables, and operators to manipulate data.
• Gain proficiency in R data structures such as vectors, factors, lists, data frames, matrices, and arrays.
• Develop the ability to write and debug R functions to perform complex data operations.
• Learn to control R workflows using conditional statements and loops for efficient data processing.
• Master the use of R packages to expand functionality and apply advanced data analysis techniques.
• Acquire skills in importing and exploring datasets within R, preparing data for analysis.
• Explore matrix operations and data frame manipulations to organize and summarize data effectively.
• Get introduced to Power BI Desktop's environment and understand the Query Editor for data transformation.
• Learn about star schema and its importance in building a structured data model for analysis.
• Create compelling visualizations and reports in Power BI, and understand how to share insights using Power BI Service and Power BI Mobile.
• Discover how to connect to various data sources and extend Power BI capabilities by creating custom visuals.