24x7 Flexible Learning with Self-Paced Videos
- Participants can access the course videos anytime and can take the course at their pace without any need for travelling anywhere
Doubt Clearing Sessions
- Live instructor-led sessions for 2 hours will be held each month exclusively for question and answers. Students can interact with the faculty or fellow students as if they are in a physical class and get their doubs resolved.
- Participants have access to the supplemental research material and detailed analysis of articles published on blogs.
- Participants will have access to student forums where they can interact and discuss the SAS and analytics concepts with fellow participants and the faculty. Student forums help you to connect with the Edzyme analytics community.
Offline Faculty Support
- Get to interact and clarify your doubts over email, phone or chat with the faculty after the classes.
Introduction to Analytics
- What is Analytics?
- Role of an analytics professional
- Popular tools used
- Overall Analytics Methodology
- Case Studies
Base SAS Language
- Reading data into SAS
- Performing operations on the data
- Working with different SAS procedures
- SAS Functions
Advanced SAS Language
- SAS Macros
- SQL in SAS
- Preparing Data for Predictive Modelling
Statistical concepts and their applications in Business
- Descriptive Statistics
- Probability Distributions
- Hypothesis Testing and ANOVA
- Application on case studies
Case studies you would be working on
Analyzing the Stock Market Data
We would learn the concepts of base SAS i.e importing the data, working with the data and so on using the stock market data on various indices
With this data we would be analyzing and preparing some custom reports to indicate performance of the indices
- We would be learning the concepts of SAS Macros with the automobile data
Furniture Sales Data
- We would be analyzing the furniture sales data while learning the concepts of SQL
Analyzing the performance of 4 cricketing legends
We would analyze the batting performance of Sachin Tendulkar, Saurav Ganguly, Rahul Dravid and Virender Sehwag
The aim of this case is to apply the concepts of descriptive statistics, hypothesis testing and ANOVA to draw inference from the data
Introduction to Analytics
You get introduced to what is Analytics? How and where is it used? We walk through why is it important? And the future of analytics from a job point of view.
Setting up the Infrastructure
Installation guide for SAS software and a walk through the LMS to download the course material.
SAS Language Fundamentals - I
You get introduced to the SAS software here, we explore different screens as in the programing editor, the log window and the results tab. We discuss in detail about the explorer, libraries. Then we get into building your own database in SAS, importing data into SAS from different sources and finally viewing the structure of the data.
SAS Language Fundamentals - II
Let's get the ball rolling! Here you work on the data, understand how to print and summarize your data. Get the know-how of different formats, creating and subsetting the data and applying the conditional logic. We analyze the stock market data while learning the SAS system.
SAS Language Fundamentals - III
Things get more interesting here, get to print custom reports in different form and play with the data by applying different summarizing procedures, we walk through different procedures in SAS to look at our data in different angles. We then conclude with different methods on merging and stacking the datasets. Throughout the session we learn in a case study framework on the stock markets data. Learning can never be such fun!
Now that the foundation is laid in basic SAS, here you dive into the advanced SAS topics. Learn how to make your code dynamic, efficient coding vis-à-vis inefficient methods and so on. We learn the concepts of SAS Macros by analyzing the automobiles data in different angles.
SQL in SAS
Data, Data Everywhere – So why not learn efficient ways on dealing with tables. Here we discuss another advanced SAS topic, SQL. We work with a Furniture sales data while learning what SQL can do in SAS. Even those who know SQL, would be amazed to see how easily it can be implemented in SAS.
Now that we've set our Launchpad in SAS, let's get prepared to deal with the nuances of data. As an analytics professional or as a SAS programmer, you would spend 90% of your time in cleaning and organizing your data. We discuss all the steps involved in doing so over here and prepare ourselves for predictive modeling. Also we understand the different types of variables and dealing with outliers, etc.
We prepare the base in statistics over the next three sessions. In this session we discuss Population and Sample and it's relevance. We then discuss various data summarizing techniques and measures.
Univariate Statistics - Hypothesis Testing
We understand the sampling distributions and various probability distributions. We then work on Testing of Hypothesis
Univariate Statistics - ANOVA
We work further on the univariate statistics, tests for normality and so on. We conclude our module on statistics with a detailed understanding of ANOVA