MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 36 lectures (1 hour, 8 mins) | Size: 224 MB

This course gives you an understanding of the application of predictive analytics in your field of interest /domain.

What you'll learn

predictive analytics

HR Analytics

Fraud Analytics

Customer Analytics

Requirements

No prerequisites

Description

PREDICTIVE ANALYTICS

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 snts 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 dаta: social media, transaction history, demographic data, e.t.c

PREDICTIVE FRAUD ANALYTICS

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.

PREDICTIVE HR 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 strat 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.

Who this course is for:

Data Analysts

Data Scientists

Business Analysts

Managers

Predictive Analytics Enthusiasts

HR Professionals

Marketers

Fraud Analytics professionals



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