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I T 104

Code Free Analytics for Non-IT Professionals and Managers

A. Objectives of the course

The objective of this course is to provide skills of using basic models of analytics using “drag and drop” configurable analytics packages without or minimal use of coding or programming. 

Products like Knime, Rapidminer, Azure ML Studio enable building sophisticated analytics models through “drag and drop” GUI. The models can be tuned by configuring the parameters through user friendly GUI screens. Cloud based platforms like AWS Sagemaker enable executing the models in production environment easily. The journey is similar to that from custom software to ERP in case of business processes.

B. Target participants

This course is designed for junior, middle and senior level business managers who have good to strong understanding of their business and want to apply basic analytics to solve their business challenges without having to learn coding. The learner needs to come from a science, commerce, economics, engineering or medicine background with reasonable understanding of high school level mathematics and statistics. 

C. Duration

15 hours (10 sessions of 90 minutes each) over a period two months

4. Pedagogy

The pedagogy of the course is based on teaching the statistical theory on which basic machine learning algorithms. Understanding of the application of the same will be developed using case studies and building prototypes of the models for those cases on analytics packages. 

D. Session details

Session No.   Topic

1.Overview of data analytics, types of data analytics – descriptive, predictive and prescriptive analytics and their use cases

2. Regression and classification fundamentals, basic understanding of linear and logistic regression, decision tree and support vector machine

3. Modeling business challenges on classification using Knime/ Rapidminer/ Azure ML Studio or similar such analytics package

4. Modeling business challenges on classification using Knime/ Rapidminer/ Azure ML Studio or similar such analytics package

5. Basic understanding of clustering (K-means and hierarchical)

6. Modeling business challenges on clustering using Knime/ Rapidminer/ Azure ML Studio or similar such analytics package

7. Data visualization using Tableau or similar such data visualization package

8. Basics of digital media analytics

9. Basics of social media analytics

10. Basics of text mining and sentiment analysis, modeling using Knime/ Rapidminer/ Azure ML Studio or similar such analytics package

F. Course Director and Core Faculty

Mr. Atanu Ghosh

Profile

Atanu is an Electrical Engineer from Jadavpur University and obtained Post Graduate Diploma in Management from the Indian Institute of Management Bangalore. He is a Visiting Faculty in several leading academic institutions like XLRI, IIM Calcutta, IIM Udaipur, etc.

Atanu is the Founder and CEO of Bluebeaks Solutions, which is engaged in education, research, consulting and training in the digital transformation domain; and Salt n Soap, an ecommerce technology and analytics platform. Before his entrepreneurial stint he was a Director with IBM and, prior to that, a Principal with PwC Consulting. Atanu has consulted various Fortune 100 companies in India, USA, UK, Singapore and China.