Master Advanced SAS Programming with Encode-IT’s SAS Advanced Online Course

SAS is one of the most widely used statistical software tools in the fields of data analysis, clinical
research, and business intelligence. SAS Advanced programming builds on foundational SAS skills,
offering a deep dive into sophisticated programming techniques, data manipulation, and complex
statistical analyses. This advanced course from Encode-IT will enhance your proficiency in SAS,
preparing you to tackle complex datasets and statistical models with confidence.

Designed for professionals already familiar with basic SAS programming, this course takes you
through advanced techniques such as macro programming, SQL in SAS, and the use of advanced
statistical procedures. You will learn to handle large datasets, optimize your code for efficiency, and
apply advanced methods for regression analysis, time series forecasting, and predictive modeling. By
the end of this course, you will have the skills required to solve complex data problems and produce
high-quality analytical results, making you a valuable asset to any organization.

Salary Prospects in India:
SAS Advanced programming skills are in high demand across various sectors, particularly in data
science, healthcare, finance, and research. Professionals with expertise in SAS Advanced can expect
a salary ranging from ₹7 to ₹15 lakhs per annum, with senior or highly specialized roles offering
salaries that can exceed ₹20 lakhs annually. The advanced skillset acquired in this course opens the
door to high-level positions such as Data Scientist, Senior SAS Programmer, Biostatistician, and Data
Analyst. The demand for skilled SAS professionals continues to grow, ensuring strong career
opportunities and lucrative salary prospects.

Placement Assistance & Certification:
Upon completing the SAS Advanced course, you will receive a Certificate of Completion from
Encode-IT, validating your expertise in advanced SAS programming techniques. Our Placement
Assistance program will support you in finding job opportunities, offering services like resume
writing, interview coaching, and direct connections with leading companies in data analysis,
pharmaceuticals, and business intelligence.

Course Curriculum:

Module 1: Advanced Data Step Programming
 Overview of Advanced Data Step Techniques
 Using Arrays and DO Loops for Complex Data Manipulation
 Efficient Sorting, Merging, and Concatenation of Large Datasets
 Advanced Methods for Data Transformation and Cleaning
 Using Functions for Enhanced Data Handling

Module 2: Macro Programming in SAS
 Introduction to Macro Variables and Macro Functions
 Creating Reusable Macro Code for Efficient Programming
 Automating Reports and Processes Using Macros

 Debugging Macro Code for Optimal Performance
 Advanced Macro Techniques: Conditional Logic, Loops, and Iteration

Module 3: SAS SQL and Data Access
 Using PROC SQL for Advanced Data Manipulation
 Integrating SQL with SAS to Query and Manage Databases
 Joining and Aggregating Data from Multiple Sources
 Advanced SQL Techniques: Subqueries, Nested Queries, and SQL Views
 Using SAS Libraries and External Databases in SQL

Module 4: Advanced Statistical Procedures in SAS
 Applying Advanced Statistical Techniques Using SAS Procedures
 Regression Analysis: Linear, Logistic, and Multivariate
 Time Series Analysis: ARIMA and Exponential Smoothing
 Survival Analysis Using SAS Procedures: Kaplan-Meier and Cox Regression
 Advanced Techniques in Hypothesis Testing and Analysis of Variance

Module 5: Predictive Modeling and Machine Learning
 Introduction to Predictive Modeling with SAS
 Building Regression Models: Linear, Logistic, and Polynomial
 Introduction to Machine Learning Algorithms in SAS
 Implementing Decision Trees, Random Forests, and Neural Networks
 Model Evaluation and Validation: Cross-validation, ROC Curves, and AUC

Module 6: Advanced Reporting and Output Delivery
 Creating Dynamic Reports with PROC REPORT and ODS
 Customizing Tables, Graphs, and Dashboards for Business Insights
 Using ODS Graphics for High-Quality Visualizations
 Exporting Results to Excel, HTML, and PDF Formats
 Automating Report Generation and Output Delivery

Module 7: Working with Large Datasets in SAS
 Optimizing Code for Handling Large Datasets
 Techniques for Efficient Memory Usage and Processing Speed
 Using PROC SUMMARY and PROC MEANS for Large Data Aggregation
 Efficient Data Storage and Management in SAS

 Parallel Processing and Multi-Core Computing in SAS

Module 8: Advanced Data Visualization Techniques
 Introduction to SAS Visual Analytics
 Creating Interactive Graphs and Dashboards
 Using PROC SGPLOT, SGSCATTER, and Other Visualization Procedures
 Visualizing High-Dimensional Data: Heatmaps, Cluster Analysis
 Combining Data Visualization with Predictive Modeling

Module 9: Data Mining and Text Analytics with SAS
 Introduction to Data Mining Techniques
 Association Rules, Clustering, and Market Basket Analysis
 Text Mining and Sentiment Analysis Using SAS
 Mining Unstructured Data with SAS Text Analytics
 Applying Data Mining Models to Real-World Business Problems

Module 10: Advanced Optimization and Simulation Techniques
 Introduction to Optimization in SAS
 Solving Linear and Nonlinear Optimization Problems
 Monte Carlo Simulations and Risk Analysis
 Optimization in Supply Chain Management and Resource Allocation
 Using SAS for Simulation of Business Processes and Financial Models

Module 11: SAS Integration with External Tools
 Integrating SAS with R, Python, and SQL
 Data Exchange Between SAS and External Platforms (Excel, SQL Server)
 Using SAS in Cloud Environments for Scalable Analytics
 Automating Data Integration with SAS Data Connect
 Leveraging APIs and External Libraries for Enhanced Functionality

Module 12: Career Development and Job Market Insights
 Career Paths in SAS Programming and Data Science
 Preparing for SAS Certification and Job Opportunities
 Resume Building and Networking in the Data Science Industry
 Interview Preparation for Senior SAS Programming Roles
 Industry Trends: Data Science, Machine Learning, and Predictive Analytics

Module 13: Final Project and Certification Exam
 Final Project: Applying Advanced SAS Programming to a Real-World Data Problem
 Project Evaluation: Demonstrating Your Advanced SAS Skills
 Final Exam: Comprehensive Test on SAS Advanced Programming Concepts and Techniques
 Certification of Completion from Encode-IT and Job Placement Assistance

Key Features of the Course:
 Tools & Platforms: SAS Software, PROC SQL, MACROS, ODS Graphics, R, Python
 Real-World Projects: Hands-on projects that address complex data problems using SAS
 Certification & Placement Support: Encode-IT certification and job placement assistance to
help you advance in your career
 Expert Instructors: Learn from industry professionals with vast experience in SAS
programming and analytics
 Career Advancement: Acquire the advanced programming skills required for senior-level
roles in data science and analytics

Completing the SAS Advanced Programming course at Encode-IT will ensure you have the advanced
skills to manage, manipulate, and analyze complex data sets, build predictive models, and generate
high-quality insights for decision-making. Whether you're seeking to advance in your current role or
pursue new opportunities in data science and analytics, this course will provide the tools and
knowledge necessary to achieve your career goals.