Data Science : Predictive Analytics Theory
Data Science : Predictive Analytics Theory | Udemy Course
Definition. Predictive analytics is an area of statistics that deals with extracting information from data and using it to predict trends and behavior patterns. ... Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining.
What you'll learn
- predictive analytics
- HR Analytics
- Fraud Analytics
- Customer Analytics
- No prerequisites
This course gives you an understanding of the application of predictive analytics in your field of interest /domain. As you learn the tools (machine learning, statistics e.t.c) its important to understand the application part. Whether you are a manager, newbie, enthusiast, data scientist or a machine learning professional, this course will bring more light on how you can apply predictive analytics in your domain.
PREDICTIVE CUSTOMER ANALYTICS
- Analyzing customer behaviour
- From focusing on segments to focusing on the individual customer
- This has been made possible through technological advancement & data mining tools
- At the highest level of using customer data is predicting customer behaviour
- Why? Lots of data: social media, transaction history, demographic data, e.t.c
- Using predictive analytics in fraud detection & prevention
- Move from detecting fraud after we have already made a loss to detecting fraud behaviour and thus prevent it from happening.
- With tech, we’re trying to go into improving UX & UI such as fewer authentications but that comes with gaps for digital fraud hence the need for predictive fraud analytics.
- We are moving to a data-driven HR function
- Why? HR collects lots of data that can be used ( demographics, salary history, empl history, promotions data, churn data e.t.c )
- Moving from depiction HR dep as a cost function to a strategic partner in the business.
- Decisions like attracting, retaining and managing talent can be backed with data and to add more applying predictive analytics in those decisions.