Certified Business Analytics Professional

Comprehensive training course on SAS and Predictive Analytics techniques

Course at a Glance

Mode of learning : Online - Instructor Lead(LVC)

Domain / Subject : Business & Management

Function : Information Technology(IT)

Starts on : 11th Oct 2014

Duration : 60 Hours

Difficulty : Medium

Through this business analytics course you will learn how to use analytical techniques and the ‘SAS programming language’ to solve business problems in a number of fields like financial services, retail, FMCG etc. This is a comprehensive course which will take you from the basics of statistical techniques and ‘SAS programming language’ right up tobuilding predictive models. By the end of this course you will be able to demonstrate your business analytics skills to employers..

The business analytics course is designed to provide a hands-on, practical experience with over 15 real world case studies and data-sets. At the end of the classroom course there will be a multi-session, hands-on simulation of an analytics solution to an actual business problem. The online self-paced learners will view videos discussing the problem and depicting the solution.

  • 60 hours (10 weekends) live, online, instructor led version of the Certified Business Analytics Professional course
  • Weekday evening and Weekend batches
  • Get the benefits of learning from your place in a fully interactive, online classroom environment
  • Interact with the instructors and fellow participants through chat, voice and video as if you are in a classroom
  • Get certified by us and also avail placement assistance
  • 24x7 lifetime access to the recorded classes and course content.
  • Download software on your own computer to practice 24x7x365.
  • Online classroom sessions will be recorded for you to revise later

Course eligibility

This course is for students pursuing their graduation/post-graduation and also for working professionals who have completed their graduation in any field. There are no other prerequisites but you do need to have a quantitative bent of mind. For those who hate maths or numbers, while we shall try to make you as comfortable as possible, the analytics field itself may prove to be a challenge for you. 

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Introduction to business analytics

In this section we shall provide you an overview into the world of analytics. You will learn about the various applications of analytics, how companies are using analytics to prosper and study the analytics cycle.

  • Business analytics in operation
  • Applications of analytics
  • Different kinds of analytics
  • Analytics cycle
  • Big data analytics
  • Case studies

Fundamentals of SAS language
This part is all about learning how to manage and manipulate data and datasets, the very first step of analytics. We shall teach you how to use the SAS language tool to work with data using a real-world case study

  • Introduction to SAS language
  • Understanding SAS programs
  • Case study on data management with SAS language
  • Reading and writing data in SAS language
  • Manipulating data with SAS language
  • Conditional statements in SAS language
  • Merging , sorting and exporting  datasets
  • Assignment and quiz

Univariate statistics

This is where you shall learn how to start understanding the story your data is narrating by summarizing the data, checking its variability and shape by visualizing it. We shall take you through various ways of doing this using the SAS language and also solve a real-world case study.
  • Summarizing data, measures of central tendency
  • Measures of variability, distributions
  • Using SAS language to summarize data
  • PROC Means, PROC Freq, PROC Univariate, box plots
  • Solving a case study using SAS language
  • Assignment and quiz

Hypothesis testing and ANOVA

With 95% confidence we can say that there is a 75% chance, people visiting this site thrice will enroll for the course :). Here, you learn how to create a hypothesis, test and validate it through data within a statistical framework and present it with clear and formal numbers to support decision making.

  • Introducing statistical inference
  • Estimators and confidence intervals
  • Central Limit theorem
  • Parametric and non-parametric statistical tests
  • Analysis of variance (ANOVA)
  • Case studies
  • Using SAS language to conduct statistical tests
  • Assignment and quiz

Data preparation using SAS language
Real world data is rarely going to be given to you perfect on a platter. It will always be dirty with missing data points, incorrect data, variables needing to be changed or created in order to analyze etc. A typical analytics project will have 60% of its time spent on preparing data for analysis. This is a crucial process as properly cleaned data will result in more accurate and stable analysis. We shall teach you all the techniques required to be successful in this aspect.

  • Needs & methods of data preparation
  • Handling missing values
  • Outlier treatment
  • Transforming variables
  • Derived variables
  • Binning data
  • SAS language functions
  • SAS language arrays and macros
  • Case studies
  • Assignments & quiz

Predictive modelling
1. Correlation and Linear regression
A statistical model is the core of predictive analytics and regression is one of the most powerful tools for making predictions by finding patterns in data. You shall learn the basic of regression modelling hands-on through real world cases

  • Correlation
  • Simple linear regression
  • Multiple linear regression
  • Model diagnostics and validation
  • Case study
  • Assignment & quiz

2. Logistic regression
Logistic regression is the work-horse of the predictive analytics world.  It is used to make predictions in cases where the outcomes are dual in nature i.e. an X or Y scenario where we need to predict if X will be the case or will Y, given some data. This is a must-know technique and we shall make you comfortable with it through real world problems.

  • Moving from linear to logistic
  • Model assumptions and Odds ratio
  • Logistic regression in SAS language
  • Real world case study
  • Model assessment and gains table
  • ROC curve and KS statistic
  • Assignment and quiz

3. Segmentation for marketing analytics
Learn why and how to statistically divide a broad customer market into various segments of customers who are similar to each other so as to be able to better target and meet their needs in a cost effective manner. This is one of the most essential techniques in marketing analytics.

  • Need for segmentation
  • Criterion of segmentation
  • Types of distances
  • Clustering algorithms
  • Deciding number of clusters
  • Clustering using SAS language
  • Real world case study
  • Assignment & quiz

Solving an actual business problem through analytics – Simulating an analytics project
Simulation of an actual analytics project where you shall be completely hands-on and you will understand how everything you have learnt so far comes together to solve a business problem through analytics.

Review and doubt solving
We shall ensure that you don’t leave without having every one of your doubts cleared




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