In this course, you will learn :
- We cover essential topics including data integrity, the four types of data analytics (descriptive, diagnostic, predictive, and prescriptive), and statistical analytical methods.
- Learners who complete this course will be able to identify the sort of data analytics approach utilised in a particular situation as well as their position in the data analytics lifecycle.
- In addition, as the tool of choice for this Nanodegree programme, this course will provide a fundamental understanding of Power BI.
- Perhaps the most crucial step in data analysis is the preparation phase. An effective data model is essential before data can be efficiently analysed, and constructing that data model may require a wide range of abilities.
- This course teaches you how to load, clean, and organise data in Power Query, as well as how to create relational tables in Power Query and Power BI.
- Learners will be able to successfully source data in Power BI and develop a clean and efficient data model for analysis after completing this course.
- introduces students to a variety of powerful tools available in Power BI Desktop for predictive analysis. Classification, regression, and forecasting are examined in depth, and various methodologies are investigated with various data sets, allowing students to practise predictive data analysis with a hands-on approach.
- This course's information can assist a firm in understanding future risk, analysing different marketplaces, or making other vital decisions.
- Intro to Data Analytics
- Data Preparation & Modeling
- Predictive Data Analysis