SAS Data Analyst Training Program In exclusive association with 21,347+ Participants 10,000+ Brands 1200+ Trainings 45+ Countries [Since 2009] Training partner for
Who Is This Course For? Programmers Non-Programmers Course Highlights Govt. of India (Vskills Certified Course) 3 hrs/week Live Instructor-Led Online Sessions Lifetime Access To Updated Content and Videos Industry and Academia Faculty 15 days of Project Work Placement Support Personalised Training Program 24X7 Support On Discussion Forum Weekly Assignments Top Analytics Tools covered Specialize in SAS Industry s Top SAS Advisors Course Advisors Vishal Mishra CEO & Co-Founder Vishal is a Technology influencer and CEO of Right Relevance. (A platform used by millions for content & influencer discovery) Manas Garg heads the Analytics for Marketing at Paypal. He takes Data Driven Decisions for Marketing Success. Manas Garg Architect
Course Instructors Aakash is an experienced SAS certified Data Integration Developer and Base Programmer with 3.5 years of experience in analysis, design, development and testing of complex distributed systems. This experience spans from working in data development, solution designing and SAS platform administration in Windows and Unix based SAS 9.3 multi-tier Architecture in Insurance domain. Dilnoor is a SAS Base and SAS Advanced Certified Professional having a total of 6 years of IT industry experience. He has built 2 startups in web and mobile domains. As an Analyst in the pharmaceutical industry, he designed SAS Solutions for Measuring the Comparative effectiveness of drugs in US population and Creating pricing models for drug launches in the European Markets. Post that in the auto insurance industry his work involved creating SAS Predictive models on insuree's risk factors and telematics data. Course Curriculum This SAS course is thoughtfully designed to allow learners with both technical as well as non-technical background to make a transition into the analytics industry with the correct skillsets. It is designed in a way that post completion of the program, learners be prepared to devise solutions for real-time problems in the industry through SAS. The course covers all the topics from SAS Base Programming Certification major coverage from the SAS Advanced Programming and essential procedures and techniques from SAS Statistical Business Analysis: Regression and Modeling INTRODUCTION TO DATA ANALYTICS An introduction topic to understand the drivers to data analytics field and its ecosystem. Introduction to Data Analytics with SAS
SAS BASE PROGRAMMING This section lays the foundation to the SAS Base Programming, starting with the basics about SAS and its architecture. These topics will help connecting with the technology for a holistic understanding. It will cover the underlying function of data step; manipulation of data through various functions and methods available in SAS. Learners will learn manipulation of data through various functions and methods available in SAS, exploring the limits of SAS and think of challenges. The important topics of SAS Procedures and error handling will be covered in depth. SAS Architecture What is SAS? Architecture of SAS and servers Understanding SAS Statements Submitting a SAS Program SAS Program Syntax Accessing SAS Libraries Using SAS Formats Reading and Accessing Data Understanding PDV and IB Options and statements Writing Observations Writing to Multiple Datasets Reading Excel Data, Raw Files, Database Data Reading from other SAS datasets Managing Data Functions in SAS Transposing Data Character and Numeric Functions Converting Variable Type Reading Formatted Input Do Loop Processing Conditional Do Loop Processing Using SAS Arrays SAS Array Processing Understanding SAS Procedures Introduction to SAS Procedures SAS Procedures to Probe, Analyse and Report The anatomy of a proc The proc statement General Purpose Proc: Proc Sort Probing Datasets: Proc Contents Probing Datasets: Proc Datasets Horizontally merging the data Data Merge SAS Procedures used for Analysing Data Proc Freq Proc Means Proc Tabulate Important Procs, Error Control and ODS Proc Print Proc Transpose Proc Compare Proc Append Proc Options Handling Errors The Output Delivery System (ODS) Introduction Understanding how the SAS supervisor checks a job Understanding how SAS processes errors Distinguishing types of errors.sas recognizes four kinds of errors: Errors: Syntax errors Execution-time errors Data errors Semantic errors Diagnosing errors Diagnosing syntax errors Diagnosing data errors Using a quality control checklist Introduction HTML, Pdf and postscript, Rtf files, Microsoft Excel
SAS ADVANCED PROGRAMMING This section will cover accessing data using SQL and SAS Macro Processing, which is an extension of advance SAS where learners will learn about macros and macro variables which is an integral part of SAS Programming. Accessing Data Using SQL Introduction to SAS's Version of SQL Integrity Contraints Performing CRUD Operations on Data Creating New Datasets and inserting data Reading from Datasets Performing Queries on Datasets Executing Advanced Queries on Datasets Combining Datasets Horizontally and Vertically Updating data in datasets Deleting Data and deleting datasets Dictionary Tables Data Analytics using R Data Analytics using SAS SAS Macro Processing - I Introduction to Macro Language Automatic Macro Variables Defining User Defined Macros Automatic vs User Defined Macro Variables How SAS Processes Macro Variables Displaying Macro Variable Values in the SAS Log Masking Special Characters Using SAS Functions with Macro Variables (29,900+ST) SAS Macro Processing - II Using Macro Variables and Macro Programs Creating Macro Variables During DATA Step Execution Creating Macro Variables During DATA Step Execution Obtaining Macro Variable Values Creating Macro Programs Using Macro Parameters Understanding Symbol Tables Processing Statements Conditionally Processing Statements Iteratively
SAS STATISTICAL ANALYSIS: REGRESSION AND MODELING, SAS VISUALIZATION This section will introduce to the topics of statistics and application of statistical analysis in regression and modelling, with Visualization techniques. Introduction to Statistics Statistics in SAS Variable Types Variable Transformations Measurement Scales Measures of Central Tendency Measures of Dispersion Shape: Skewness Shape: Kurtosis Sampling Correlation and Causation Multicollinearity Hypothesis Testing SAS Visualization Explolatory Data Analysis Scatterplot Histogram BoxPlot Proc sgplot Bar Chart Line Charts Scatter Plot Stacked Column Bubble Charts Cycle Plots SAS Modelling Regression Techniques Logistic Regression Linear Regression Essential Differences Mathematical foundation SAS Modelling Continued Data Preparation Data Collection Modeling and Validation Split EDD Data Prep: Outlier Treatment Capping and Flooring Technique Smoothing Techniques Sigma Approach Robust Regression Technique Mahalanobis Distance Technique Data Prep: Missing Value Treatment Assign Missing Values with ZERO Assign Missing Values with MEDIAN Assign Missing Values with MEAN Assign Missing Values with MODE Post Outlier Treatment Identify Unrequired Variables Reformating Variables Model Demostrations Proc Reg Proc Logistic
Projects (3 Weeks) Slice and dice dataset to extract valuable insights and apply an entire range of skill sets learnt in this course. Tool Project 2: Data Visualization Project Duration Fee Batch Options 17 Weeks Rs. 34,900+GST Weekend Interested? Contact Us! +91-84680-02880 info@digitalvidya.com www.digitalvidya.com Attend a Free Orientation Session: http://www.digitalvidya.com/data-analytics-course