In today’s business environment where “ the world’s most valuable resource is no longer oil but data”, businesses need more and more people with skills to extract insights from data and turn it into profit potential. Decision based on emotions, opinions and biasness leads to a horrible result causing your business millions of loss and waste of effort and time however, with data science, your decisions and problem solving skills will be better and faster as they will be based on reliable sources, predictions, analysis, interpretation and optimization. Whether you are from a logistics, retails, marketing and advertising, financial or any industry, data science is being used for business intelligence, for improving products, for increasing the management capabilities of companies and for predictive analytics.

For instance: Walmart, being the world’s largest retailer, is one of the many major industries that is leveraging Big Data to make business more efficient. A staggering amount of about 2.5 petabytes of data is collected from the customers every hour. It tracks and monitors various factors that might affect the sales at Walmart stores.

The concepts covered in this course will enable the participants to clean and analyses data, build models for prediction, create interactive data visualizations, and to learn practical application in industrial context.

Who is it for?

Everyone actually!

Mid-level professionals, Change makers, Product developers, Strategist, marketers, Entrepreneurs, Business / Engineering and Design Students.

This way of thinking can be applied to products, services, and processes; anything that needs to be improved or disrupted, by focusing on creating excellence in customer experience.

Learning Outcomes:

ü  Focuses on strategic aspect of business problems

ü  Carefully crafted approach to provide students with a thorough understanding of business cases in the organizations’ context.

ü  Case studies spanning across various functions of an organization for a 360-degree view.

ü  Designed for programmers and non-programmers both in mind with focus on strategic aspect of data analytics

ü  Completely hands on approach

 Key Highlights

ü  40 HRS - Instructor led session 

ü  Batch of 35-40

ü  Theory to practical ratio: 20:80

ü  Each module will have two case studies as a part of training delivery

ü  KPMG in India will guide participants in selecting and completing a capstone project as a part of this training delivery.  

ü  A group project or an individual project depending on batch size.

 

Modules Covered 

ü  Use R and Python to clean and analyze data

ü  Use inferential and descriptive statistics to make business decisions

ü  Create dashboards and stories

ü  Build real-time predictive models using appropriate techniques

ü  Fetch data from websites for analysis

ü  Determine customer sentiment by analyzing feedback/reviews

ü  Automate repetitive analytics tasks

 

Coverage

ü  Packages and syntax for data science (R and Python)

ü  Business statistics for decision making

ü  Data wrangling using R

ü  Visualization using dashboard and stories in Tableau

ü  Predictive modeling using Python

ü  Text and sentiment analysis using Python

ü  Web scrapping using Python