Data Science of Experimental Design Training Programme

Why Attend

Power BI is an analytics tool developed by Microsoft that transforms unstructured data into visually compelling narratives. This course offers training on Power BI, which includes Power BI Desktop, the SaaS Power BI Service, and various mobile apps compatible with iOS and Android. These tools enable businesses and organizations to ask the right questions and gain actionable insights from large amounts of data.

Power BI consolidates information from diverse data sources and creates custom visuals, helping organizations not only interpret the data but also understand the best course of action. Effective data visualization can mean the difference between data that fades away and data that informs critical, accurate decisions.

As one of the most robust business intelligence platforms available for data modeling, Microsoft Power BI utilizes real-time dashboards to process and present data from multiple sources. This functionality provides businesses with better insights into their customers, operations, and future prospects.

Gaining proficiency in Power BI and DAX through allows you to deliver real value to a business, moving beyond just gathering numbers. Whether dealing with simple Excel files, SQL servers, or complex collections of on-premises and cloud data, Power BI has the capability to streamline and organize it all.

Course Objectives

By the end of the course, participants will be able to:

This course offers this course to the following categories:

• All six-sigma practitioners.
• Scientists, engineers, and technicians who are interested in performing experiments that maximize process knowledge with a minimum amount of resources. 
• Managers who are responsible for delivering products “on time” and “on budget”.
• Students, novice programmers, and any professionals who interact with data.
• Analytics managers.
• Undergraduate students who need to run and analyse experimental data.
• Anyone interested in designing, conducting, and analysing experiments.

After completing the program, participants will be able to master the following topics:

• Prepare data for effective analysis.
• Use data science to design experiments to be as informative as possible.
• Optimise experiments to save time and money
• Use laboratory automation and robotics to reduce research biases.
• Make research more reproducible.
• Identify the obstacles to integrating data-driven experimental design in real laboratories, from an ethnographic and sociological perspective.
• Analyse the data, and make decisions based on the results of the test.
• Learn about robotic laboratories and their effect on future of experimental research.