SAS Predictive Modeling – (3 in 1) with 3 live Case Studies

SAS Predictive Modeling – (3 in 1) with 3 live Case Studies, available at $49.99, has an average rating of 3.5, with 45 lectures, based on 56 reviews, and has 1936 subscribers.

You will learn about Linear Regression, Logistic Regression &Time Series Forecasting Live Project on Linear Regression, Linear Regression, Logistic Regression &Time Series Forecasting Business Analytics in Short and Why it is So much Important Now a Days! Multi Collinearity and Auto Corelation ODDS AND ODDS Ratio Concordant Pairs,Discordant Pairs and Tied Pairs Setting the Cut Point Probability Level Confusion Matrix Smoothing Technques Stationarity and Non-stationarity ARIMA Modelling BOX JENKINS Technology This course is ideal for individuals who are Intermediate SAS user or People who wants to get insight into data and want to predict the future outcome from the data or Data Science Enthusiastics It is particularly useful for Intermediate SAS user or People who wants to get insight into data and want to predict the future outcome from the data or Data Science Enthusiastics.

Enroll now: SAS Predictive Modeling – (3 in 1) with 3 live Case Studies

Summary

Title: SAS Predictive Modeling – (3 in 1) with 3 live Case Studies

Price: $49.99

Average Rating: 3.5

Number of Lectures: 45

Number of Published Lectures: 45

Number of Curriculum Items: 45

Number of Published Curriculum Objects: 45

Original Price: $69.99

Quality Status: approved

Status: Live

What You Will Learn

Linear Regression, Logistic Regression &Time Series Forecasting
Live Project on Linear Regression, Linear Regression, Logistic Regression &Time Series Forecasting
Business Analytics in Short and Why it is So much Important Now a Days!
Multi Collinearity and Auto Corelation
ODDS AND ODDS Ratio
Concordant Pairs,Discordant Pairs and Tied Pairs
Setting the Cut Point Probability Level
Confusion Matrix
Smoothing Technques
Stationarity and Non-stationarity
ARIMA Modelling
BOX JENKINS Technology

Who Should Attend

Intermediate SAS user
People who wants to get insight into data and want to predict the future outcome from the data
Data Science Enthusiastics

Target Audiences

Intermediate SAS user
People who wants to get insight into data and want to predict the future outcome from the data
Data Science Enthusiastics

** THIS COURSE IS FOR INTERMEDIATE LEVEL SAS PROGRAMMER. DO NOT BUY THE COURSE IF YOU ARE A BEGINNER **

Why this Course is Different?

This course is NOTlike the Other Courses Over the Internet! As you have knowledge in Base SAS so this course will take you to the Intermediate and Advance Level. We will cover all the Hard Things in a easy to understand and Simple Way.

Linear Regression, Logistic Regression, Time Series Forecasting we will cover all the 3 Predictive Modeling Technique Step by Step.

After Each Chapter We cover ONE Industry Level CASE Study and 3 Case Studies in Total.

What Exactly SAS Predictive Modeling Is?

Simply Predictive modeling is a process that forecasts outcomes and probabilities through the use of data mining.

Why Predictive Modeling is Important?

It helps Organization / Business to Predict the Future Outcome from the Past Data. Which helps the Organization to make Better decision and Sales.

How Much Salary SAS Programmer is Getting?

In USA SAS Programmers are getting anywhere between $88,000 – $100,000/yr.

Job Demand For SAS Programmer?

Job Demand in SAS is Sky High. All the top Companies are using Predictive Modeling for future Outcome.

Companies Like Facebook, Google, AirBnB, Amazon, Flipkart, Alibaba all are Hiring Experts having Experience in Predictive Modeling. Technique

This course gives an overview of All SAS Predictive modeling Solution and Specifically introduces the functionality in the SAS High Performance Statics for Predictive Modeling.

This course shows examples of applying advanced statics to huge volumes of data and draw specific interpretations out of it.

Who Should take the Course?

This is an intermediate course designed for whom are comfortable with Base SAS can take the course

Course Curriculum

Chapter 1: Overview Of the Course

Lecture 1: Course curriculum Overview

Lecture 2: Download the Course Curriculum

Lecture 3: What is the Benifit of the Course?

Lecture 4: Who should take the course?

Lecture 5: Meet Your Instructor

Lecture 6: Install the Software into your System and Setup Part #1

Lecture 7: Install the Software into your System and Setup Part #2

Lecture 8: Install the Software into your System and Setup Part #3

Chapter 2: Introduction to Business Analytics

Lecture 1: What is business Analytics

Lecture 2: What are the three main categories of Analytics?

Chapter 3: Linear Regression-Practical sessions

Lecture 1: Concept of Linear Regression

Lecture 2: Assumptions of Classical Linear Regression Model

Lecture 3: Concept of Multi colinearinty and Auto corelatio

Chapter 4: Linear Regression-Practical sessions

Lecture 1: Case study discussion and Dataset descriptions

Lecture 2: DOWNLOAD : All Codes + Data Sets

Lecture 3: Linear Regression (Practical 1)

Lecture 4: Linear Regression (Practical 2)

Lecture 5: Linear Regression (Practical 3)

Lecture 6: Linear Regression (Practical 4)

Lecture 7: Linear Regression (Practical 5)

Chapter 5: Logistic regression – Concepts

Lecture 1: Concept of Logistic Regression

Lecture 2: Asumptions of Logistic Regression

Lecture 3: ODDS AND ODDS Ratio

Lecture 4: Concordant Pairs,Discordant Pairs and Tied Pairs

Lecture 5: Setting the cut point probability level

Lecture 6: Confusion Matrix

Chapter 6: Logistic regression-Practical Session

Lecture 1: Case Discussion and Dataset Description

Lecture 2: DOWNLOAD : All Codes + Data Sets : Logistic Regression

Lecture 3: Logistic Regression ( Practical Part 1 )

Lecture 4: Logistic Regression ( Practical Part 2 )

Lecture 5: Logistic Regression ( Practical Part 3 )

Lecture 6: Logistic Regression ( Practical Part 4 )

Lecture 7: Logistic Regression ( Practical Part 5 )

Chapter 7: Time series forecasting Concept

Lecture 1: Concept of Time Series Analysis

Lecture 2: Components of Time Series Analysis

Lecture 3: Smoothing Technque

Lecture 4: Stationarity and Non-Stationarity

Lecture 5: ARIMA modelling

Lecture 6: BOX JENKINS Technology

Chapter 8: Time Series Forecasting Practical Session

Lecture 1: Case Study and Dataset discussion

Lecture 2: DOWNLOAD : All Codes + Data Sets : Time Series Forcasting

Lecture 3: Time Series (Practical Part 1)

Lecture 4: Time Series (Practical Part 2)

Lecture 5: Time Series (Practical Part 3)

Chapter 9: BONUS : WHAT NEXT

Lecture 1: Bonus : What Next

Instructors

Up Degree
New Skills Everyday!

Rating Distribution

1 stars: 3 votes
2 stars: 7 votes
3 stars: 11 votes
4 stars: 17 votes
5 stars: 18 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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