| Course Duration | 40 hours Video + Practice and Study Material |
| Tools | SAS University Edition / SAS Enterprise Guide / SAS OnDemand For Academics |
Predictive Modeling with SAS
SAS (Statistical analysis system) is one of the most popular software for data analysis and statistical modeling. Knowing SAS is an asset in many job markets as it holds largest market share in terms of jobs in advanced analytics.
SAS has over 40,000 customers worldwide and holds largest market share in advanced analytics. It has been tagged ‘leader’ consistently in advanced analytics platform as per Gartner 2015, 2016 and 2017 reports.
Through this online training course you will get hands-on experience to learn the practical implementation of predictive modeling techniques using real world datasets. You will also acquire banking domain knowledge.
Features!
- Faculty Support : Get your doubts cleared
- Live Project & Case Studies using real world datasets
- Industry ways of solving problems
- Simplify predictive modeling techniques via excel sheet demos
- SAS Macros to automate predictive modeling
- Interview Preparation
- Money Back Guarantee
Who Should do this course?
This course is ideal for candidates who want to make a career in advanced analytics and predictive modeling.
Any candidate pursuing graduation / post graduation or already graduate can apply for this course. No prior programming or statistics knowledge is required before enrolling for this course.
Testimonial
The course is well organized in terms of content and delivery. The instructor is well-versed with the ability to explain complex issues to the ordinary mind. I would highly recommend this course to anyone who wants to become a Data scientist with practical experience. You will have a hands-on real-world project to prepare you for your job.
I always aspired for working in data science. This aspiration turned into reality once I enrolled for Predictive modeling and data science course at listendata. The faculty at listendata focuses a lot on conceptual clarity making difficult topics very easy to understand. The best part of listendata training is emphasis on all practical aspects of predictive modelling using SAS and R. I am very thankful to Deepanshu for guiding me at every step which enabled me to crack toughest analytics interviews with flying colors. The faculty makes sure that each student queries are answered.
Curriculum - Predictive Modeling with SAS
- Introduction to Statistics & Modeling
- Applications of Predictive Modeling in various Industries
- SAS Programming - Basics
- Descriptive Statistics with SAS
- Hypothesis Testing with SAS
- Correlation Analysis with SAS
- Steps of Predictive Modeling
- Data Preparation in Predictive Modeling
- Variable Selection Methods in Predictive Modeling
- Segmentation - Introduction
- Segmentation - Cluster Analysis : Theory
- Segmentation - Cluster Analysis : Data Preparation
- Segmentation - Cluster Analysis : k-means and Hierarchical
- Segmentation - Cluster Analysis : Cluster Performance
- Principal Component Analysis (PCA) - Theory
- Running and Understanding PCA with SAS
- Linear Regression - Theory
- Linear Regression - Assumptions and Treatment
- Linear Regression - Important Metrics
- Linear Regression - Variable Selection Methods
- Linear Regression - Model Development
- Linear Regression - Model Validation
- Linear Regression - Model Performance
- Linear Regression - Model Scoring
- Linear Regression - Model Implementation
- Logistic Regression - Theory
- Logistic Regression - Assumptions and Treatment
- Logistic Regression - Important Metrics
- Logistic Regression - Variable Selection Methods
- Logistic Regression - Model Development
- Logistic Regression - Model Validation
- Logistic Regression - Model Performance
- Logistic Regression - Model Implementation
- Decision Tree - How it works
- Decision Tree - Model Development
- Decision Tree - Model Validation
- Decision Tree - Model Performance
- Decision Tree - Model Implementation
- Time Series Forecasting - Theory
- Time Series Analysis with SAS
- Special Cases - Handle rare event model
- Theory - Banking Domain Knowledge
- Case Studies - Propensity to Buy Model (Banking)
- Case Studies - Attrition / Churn Model (Telecom)
- Case Studies - Customer Segmentation I (Banking)
- Case Studies - Customer Segmentation II (Banking)
- Case Studies - Probability of Default (PD) Modeling
- Case Studies - Employee Attrition (Human Resource)
- Case Studies - Time Series Forecasting (Sales)
- Live Project - Attrition / Churn Model (Banking)
- SAS Macros to automate various Predictive Modeling Steps
- Interview Tips - Common Interview Questions
- 75+ Statistical Business Analyst Certification Questions
- Mock Interview
Case Studies
Propensity to Buy Model
To identify customers who are most likely to buy fixed deposit product. Create strategies to implement predictive model.
Probability of Default (PD) Model
To identify the bad customers with high likelihood to default on credit card payment. Build scorecard for the same.
Customer Segmentation
Segment retail bank customers based on historic activity patterns. It was used to improve contact strategies in the marketing department.
Customer Segmentation for Credit Card Holders
Customer segmentation to define sales and marketing strategy for credit card holders.
Key Drivers Analysis - Boosting Credit card Usage
To identify the factors that push the total spend of credit card.
Sales Forecasting
To forecast the next 3 months sales of a retail store.
Customer Attrition (Churn) Model - Telecom
To identify customers who are most likely to leave the telecom provider. Phone number portability makes it easy for customers to switch mobile phone services to providers.
Predictive Employee Attrition Model
To predict attrition numbers through employees responses and their demographic information.
Live Project
Customer Attrition (Banking) - Identify customers that are more likely to leave the bank.
I. First you need to create the analytics data mart using the following data sources.
- Demographic and customer baseline data
- Data on customer accounts
- Leasing data
- Data on call center contacts
- Data of value segment scores
- Student also needs to think of the plausibility of the created numbers in the data set.
II. You need to create dependent variable based on some logic.
III. You need to do feature engineering for prediction.
IV. Develop and Validate Model
V. Build Strategies - How stakeholders would utilize the model.
What You will Get
FAQs
I never studied statistics and SAS programming during graduation. Can I still enroll for this course?
Yes, the course was designed to keep in mind the needs of people without statistics background. Basics of SAS Programming will be covered so that people having no knowledge of SAS feel comfortable. Only prerequisite is hard work and zeal for learning.
For how long are the videos and course material available to me?
You will get 24*7 life-time access to recorded classes and course material on our learning management system
What kind of career assistance does ListenData offer?
We have a solid network of analytics professionals in the field of analytics and data science. We are constantly in touch with various companies and job consultancy firms for hiring. We will keep you informed about current openings in analytics industry.
In addition, we provide assistance in the following areas.
- Interview Preparation using extensive practical interview questions
- Resume Building
- Mock Interviews
Can I download the recordings and course material?
Yes, you can download soft copy, code and datasets of each lessons of the course. To access recorded videos, you need to login to your account on Learning Management System (LMS)
Downloading of videos is not allowed as it may lead to distribution of videos illegally. Illegal downloading is against ListenData acceptable use policy and can result in disciplinary action.
Will I get a certificate in the end?
Yes. All our courses are certified. As part of the course, students get weekly assignments and live project. Once all your submissions are received and evaluated, the certificate shall be awarded.
How can I reach out to someone if I have doubts post class?
You can connect with instructor via email, discussion forum or scheduled phone call. Learning Management System (LMS) has a discussion forum where you can post your questions and instructor will get your doubts cleared.
What is the refund policy?
We offer a full refund up to 3 days post your enrollment if you would like to cancel, though with such a good deal we wonder who would!No question asked refund policy!
After payment, when will I get access to the course?
After payment you will get access to the course immediately.
What are the different modes of payment available for enrollment?
Indian users can pay through net banking, debit card or credit card. Non-Indian users can pay via credit card or PayPal.
How to download and install software?
We will provide you instruction guide to download and install software. In case you still find difficulty, you can send your queries via email and discussion forum.
System Requirement : Minimum 4GB RAM