The Course Structure has been designed by internationally acclaimed faculty. The complete course has been structured to stress upon applied aspects of theory and concepts. We are very much aware of the varied educational background of Managers. And this being so, face-to-face lecture delivery and laboratory work provide us an opportunity to modulate and steer our course as per the needs and requirements of managers. We complement our face-to-face lectures with material available online. This allows students to reinforce their classroom learning at leisure within their home/office environment.
The Institute has acquired and established a State-of-Art Big Data (Cloudera system) and Data analytics laboratory that makes it very easy for a manager even from non-science background to learn and practice techniques of Data Visualization and Data Modeling using Graphical User Interfaces. Engineers at FORE have custom designed a Virtual Machine (VM) installable on laptops and richly loaded with analytics software (RStudio, Anaconda, H2O...) including complete Hadoop-eco system. VM is given to each participant at the start of the program to enable him to practice data science at home/work-place.
Our faculty and students have executed a number of projects on Kaggle. A sample list of projects can be seen in the downloadable e-book here.
This course is about knowledge discovery in databases; searching through large volumes of raw data to find useful information-patterns that are implicitly embedded in the raw data. Marketers can use this information for new sources of advantages and differentiation. The course content includes in detail Analytical techniques on Hadoop-ecosystem. Details about the course are here... Read more
Businesses are increasingly becoming complex due to changing dynamics. Knowledge and understanding of statistical methods and tools prove useful for analyzing business problems and result in effective management decision leading to business success. Based on a data-analytic approach, the course aims at cultivating in students logical reasoning and critical thinking necessary for interpreting statistical data for proper decision making. The focus of the Course is application of statistical methods and tools to problem solving...Read more
Learning outcomes for this course are (a) Ability to interpret various customer metrics, such as, Customer Life Time Value, Satisfaction Index, and Customer profitability. (b) Understand strategic implications of customer valuations, cost, revenue and profit, (c) To be able to develop strategies for customer acquisition and retention/attrition based on deeper customer data and insights, (d) Develop marketing strategies based on insights from customer analytics...Read more
Marketing environment has become very complex both online and offline. This complexity is also reflected in the variety and sophistication of tools that attempt to dissect marketing data from various perspectives and construct appropriate models. This course attempts to simplify the selection and application of dissection and modeling process in differing circumstances; it attempts to bring these technologies at the door-steps of a common man. It is divided into three modules. Module I covers basic building blocks of marketing data analysis and some important statistical predictive tools, Module II takes the study to a higher level attempting to analyze marketing data generated in digital world. Module III is about simulating real world marketing conditions in lab and deciding upon marketing strategies...Read more
This module is optional and has been introduced considering that python is emerging fast as another preferred tool for data scientists. There will be extra sessions for covering this module. Days and timing of classes will be fixed after discussion with the participants...Read more