Master Predictive Analytics with SAS Predictive Modeling: Elevate Your Data Science Career with Encode-IT

In today’s data-driven world, businesses are increasingly turning to predictive modeling to forecast
future trends, optimize processes, and make data-driven decisions. SAS Predictive Modeling is a
powerful toolset that enables professionals to build accurate models using advanced statistical and
machine learning techniques. The SAS Predictive Modeling course at Encode-IT provides a deep dive
into predictive analytics, teaching you how to create and evaluate models that predict outcomes
with high accuracy.

Throughout this course, you will learn how to leverage SAS tools, including SAS Enterprise Miner and
SAS Viya, to develop predictive models that can uncover hidden patterns in data. You’ll gain
expertise in key areas such as regression analysis, classification, clustering, and time series
forecasting. This course is designed for aspiring data scientists, business analysts, and anyone
interested in mastering predictive modeling techniques to solve real-world problems.

By the end of this course, you will be able to build, test, and deploy predictive models that can
forecast business outcomes, enabling you to support strategic decision-making and gain a
competitive edge in any industry.

Salary Prospects in India:
In India, professionals skilled in SAS Predictive Modeling are in high demand due to the growing
reliance on data-driven decision-making across industries. The salary range for individuals with
expertise in predictive analytics typically ranges from ₹8 to ₹20 lakhs per annum, depending on
experience, role, and industry. Senior positions such as Data Science Manager or Predictive Analytics
Consultant can command salaries exceeding ₹25 lakhs annually. As predictive modeling continues to
gain importance, professionals with SAS skills will see continued demand and lucrative career
opportunities.

Placement Assistance & Certification:
Encode-IT offers comprehensive Placement Assistance, helping you connect with leading companies
seeking professionals in predictive analytics and data science. Our placement services include
resume building, interview preparation, and job referrals to top organizations.

Upon successful completion of the course, you will receive a Certificate of Completion from Encode-
IT, showcasing your expertise in SAS Predictive Modeling. This certification will help you stand out to
employers and validate your skills in predictive analytics and statistical modeling.

Course Curriculum:

Module 1: Introduction to Predictive Modeling and SAS
 Overview of Predictive Analytics and its Role in Business Decision-Making
 Introduction to SAS Predictive Modeling Tools: SAS Enterprise Miner, SAS Viya
 Understanding the Predictive Modeling Process: Data Preparation, Model Building, and
Evaluation
 Overview of Supervised and Unsupervised Learning

 Key Statistical Concepts for Predictive Modeling

Module 2: Data Preparation and Exploration
 Importing and Managing Data in SAS for Predictive Modeling
 Cleaning and Preprocessing Data: Handling Missing Values, Outliers, and Normalization
 Feature Engineering: Creating Predictive Variables and Selecting Features
 Exploratory Data Analysis (EDA): Visualizing Data and Identifying Patterns
 Data Transformation Techniques: Scaling, Encoding, and Dummy Variables

Module 3: Regression Analysis for Predictive Modeling
 Introduction to Regression Analysis in SAS
 Simple and Multiple Linear Regression Models
 Evaluating Regression Models: R-squared, Adjusted R-squared, and Residual Analysis
 Logistic Regression for Binary and Multinomial Classification
 Model Validation Techniques: Cross-Validation and Holdout Validation

Module 4: Classification Techniques in SAS
 Introduction to Classification Models: Decision Trees, Random Forests, and Support Vector
Machines
 Building Classification Models using SAS Enterprise Miner
 Evaluating Classification Models: Confusion Matrix, Accuracy, Precision, Recall, and F1-Score
 Overfitting and Underfitting in Classification Models
 Tuning Model Parameters for Better Performance

Module 5: Clustering and Segmentation
 Introduction to Clustering in Predictive Analytics
 K-Means Clustering: Algorithm and Implementation in SAS
 Hierarchical Clustering and its Applications
 Evaluating Clustering Models: Silhouette Score and Cluster Validation
 Customer Segmentation and Market Basket Analysis using Clustering

Module 6: Time Series Forecasting
 Introduction to Time Series Data and Forecasting
 Building Time Series Models using SAS Forecasting Techniques
 Autoregressive Integrated Moving Average (ARIMA) Modeling
 Evaluating Time Series Models: Mean Absolute Error (MAE), Root Mean Squared Error
(RMSE)

 Advanced Time Series Models: Exponential Smoothing and Seasonal Decomposition

Module 7: Advanced Predictive Modeling Techniques
 Ensemble Learning Techniques: Bagging, Boosting, and Stacking
 Building and Evaluating Ensemble Models in SAS
 Support Vector Machines (SVM) for Classification and Regression
 Neural Networks for Predictive Modeling: Basics and Applications
 Dimensionality Reduction: Principal Component Analysis (PCA)

Module 8: Model Deployment and Performance Monitoring
 Deploying Predictive Models into Production Environments
 Model Monitoring and Performance Tracking
 Updating and Retraining Models Based on New Data
 Using SAS Model Manager for Model Deployment and Lifecycle Management
 Best Practices for Model Interpretation and Explainability

Module 9: Real-World Applications of Predictive Modeling
 Predictive Modeling in Finance: Credit Scoring and Risk Assessment
 Customer Behavior Prediction in Marketing and E-Commerce
 Predicting Equipment Failures in Manufacturing and Operations
 Fraud Detection in Financial Transactions using Predictive Analytics
 Case Study: Building a Predictive Model for a Business Problem

Module 10: Final Project and Certification Exam
 Final Project: Building an End-to-End Predictive Model for a Business Problem
 Model Building, Validation, and Deployment in a Real-World Scenario
 Project Evaluation: Showcasing Your Skills and Expertise
 Certification Exam: Comprehensive Test on Predictive Modeling Using SAS
 Certification of Completion from Encode-IT and Placement Assistance

Key Features of the Course:
 Tools & Platforms: SAS Enterprise Miner, SAS Viya, SAS Studio, SAS Model Manager
 Real-World Projects: Hands-on experience with regression, classification, time series
forecasting, and clustering
 Certification & Placement Support: Encode-IT certification and job placement assistance to
help you kick-start your career in predictive analytics

 Expert Instructors: Learn from industry professionals with extensive experience in predictive
analytics and data science
 Career Advancement: Master the skills required for roles in data science, predictive
analytics, and business intelligence

By completing the SAS Predictive Modeling course at Encode-IT, you will gain a comprehensive
understanding of advanced statistical and machine learning techniques to solve real-world
problems. You will be equipped to build, evaluate, and deploy predictive models that provide
valuable business insights, making you an indispensable asset to any organization.