Power BI is a cloud-based analytics service from Microsoft. It can be used to visualize and analyze data, with better speed and efficiency. Along with visualization advantages, Power BI has amazing out of the box connection capabilities and easy integration with Databases. Power BI provides an optimized, live connector to SQL Server so that we can easily create charts, reports, and dashboards by directly working with a large amount of data. These functionalities of Power BI comes in handy for Data Scientists who are used to working in SQL. Join us on March 16, 2024 (Saturday), 9:00 am - 5:00 pm CST (attendance online only) for a short course on Power BI & SQL for data science.
Course topics will include:
- Basic building blocks of Power BI
- How to get data in Power BI
- Data cleaning and data preparation with Power BI
- Doing analytics in Power BI
- Automated machine learning in Power BI
- Creating Dashboards and Reports in Power BI
- SQL and Power BI to analyze databases
Course Instruction Mode:
The course will be completely online and synchronous. The participants can learn all materials from the comfort of their home or any chosen location. All instructions will be live and there will be a live Q&A interactive session where students can ask question to the instructor. You need to have a Microsoft (free) account to access the Power BI Service tool. This is cloud-based tool, and no download and installation are necessary on your local machine. The Power BI service has a free version which we will use in the course. Visit https://app.powerbi.com/ to make sure you have access to this tool.
About the Instructor
Dr. Sounak Chakraborty is an Associate Professor in the Department of Statistics, University of Missouri. His research interests are Bayesian machine learning, variable selection in high dimensional problems, data mining, non-linear models for complex data sets, statistical models for multi-platform data integrations, and Markov chain Monte Carlo driven computational models. He had worked on wide ranging applications of statistical models and tools in areas as bioinformatics, medical science, sociology, ecology, business analytics, biomedical engineering, nanotechnology and nanoscience. Prof. Chakraborty is highly proficient in R, Matlab, SAS, C++, and Python, and has worked extensively in developing and implementing complex statistical models using R, Matlab, C++, and Python in various practical areas.
Course Fee Structure:
- University of Missouri System Students (undergrad and grad): $20
- University of Missouri System Faculty and Staff: $50
- Non-University of Missouri System Academic: $100
- General Admission Non-Academic: $250
Virtual “seats” are limited so register as soon as possible.
Instruction details about how to login and all course related materials to be distributed through e-mail to all registered participants on March 15, 2024. Enrollment will be closed on 03/15/2024 12 PM US Central time.
