Business Analytics & Data Science

According to a recent Wall Street Journal, companies, barraged with data from the Web and other sources, want employees who can both sift through the information and help solve business problems. As the use of analytics grows quickly, companies will need employees who understand the data.

A recent study by Edvancer & AIM reveals that number of analytics jobs doubled from April 2016 to April 2017. A May 2011 study from McKinsey & Co. found that by 2018, the U.S. will face a shortage of 1.5 million managers who can use data to shape business decisions.

Roles across Industries

The use of Business Analytics and Data Science is widespread across all industries and functions, including Information
Technology, E-commerce, Healthcare, Banking & Financial Services, HR.

Some of the application areas include product analysis, Online Behavior, customer lifecycle management, customer
service, social media connect, fraud detection, etc

  • Business Analyst
  • Financial Analyst
  • Web Analyst
  • Social Media Analyst
  • Data Scientist
  • Retail Analyst
  • Pricing Analyst
  • Fraud Analyst

Companies Hiring for these roles:

Modules Covered

  • Module 1: Advanced Excel
  • Module 2: Structured Query Language (SQL)
  • Module 3: Basics of R and Data Analysis, Data Cleaning and preparing data for analysis in R Language
  • Module 4: Measures and spread, CLT, Different Types of Test, HT and Tests, Bivariate Analysis, ANOVA
  • Module 5: Linear Regression
  • Module 6: Logistic Regression
  • Module 7: Classification Trees and Random Forest
  • Module 8: Supervised & Unsupervised Algorithm
  • Module 9: Market Basket Analysis
  • Module 10: Time Series Modelling

Program Highlights

60 Hours – Classroom Training

IIT Alumni as Faculty

Analytical Tool – R Software

Decade of Industry Experience

Hands-on Training | Capstone Project

Quality Content

Placement Assistance

Certificate of Excellence

1 Step 1

What You’ll learn:

  • Introduction to Data Analytics
  • How organizations benefit from adopting Analytics
  • Build Models to predict future outcomes
  • Case Studies