Data Science Meets Power BI: Transforming Data into Insights

Master Python, R, and Power BI: Comprehensive Data Analytics and Visualisation Techniques for the Modern Analyst

Created by: Enterprise DNA
Future-Proof Your Career: Master Data Skills | Upskill in AI

Created by: Sam McKay
Unleashing Potential: The Power of Data Mastery

What Will I Learn?

• Master integration of Python and R into Power BI for enhanced data analysis and visualizations.
• Acquire skills in using IDEs for script creation, testing, and debugging in Python and R.
• Understand how to apply Natural Language Processing (NLP) concepts and handle large datasets effectively.
• Gain expertise in creating custom functions, performing advanced statistical analyses, and creating intricate visualizations not native to Power BI.

Requirements

• Basic familiarity with Power BI and its functionalities.
• An understanding of descriptive and inferential statistics is helpful but not necessary.
• A personal computer with internet access to download the necessary software (Python, R, Power BI, and relevant IDEs).
• No prior coding knowledge is required, making the course accessible for beginners interested in data analytics.

Target audience

• Beginners in Data Science: Aspiring data scientists with little to no coding experience will find this course valuable as it provides a solid foundation in Python, R, and Power BI.
• Power BI Users: Individuals already using Power BI for data analysis and visualization, but looking to enhance their capabilities by integrating Python and R for more advanced statistical analysis and data visualizations.
• Data Analysts: Professionals already working in the field of data analysis who want to broaden their skill set with the use of Python, R, and Power BI.
• Business Intelligence Professionals: Those involved in BI who want to augment their analysis skills and deliver deeper insights using Power BI, Python, and R.
• Students: Individuals studying fields like computer science, statistics, or business who want to complement their academic knowledge with practical, industry-relevant skills in data science and visualization.