DataHour: Using Data Science Methodology to Assess Equity in Communication

In current times, social media connections are being used to find suitable candidates for hiring in an organization or sharing a new product with prospective partners and clients. But have you realized whether you are reaching your target audience or not? And is it free from gender equity? How do you analyze your data before taking action to make sure your communication is not biased? 

For answering all such questions AI techniques are being used nowadays as it is increasingly offering predictive analysis. But Do you know the steps needed for developing and optimizing these AI models?  Also, can we develop predictive insight without extensive programming? Answers to all such questions will be found in this session. 

In this DataHour, Arvind and Neena, will introduce you to data science methodology in the context of developing a predictive model for LinkedIn connections analysis. To keep the focus on key tasks, no code tools will be used, and additional resources for using these no code tools for AI model development will be shared. 

 

Prerequisites: Interest in Data science and AI and a zeal to learn something new.

Neena Sathi is a principal at Applied AI Institute. She has 30+ years of experience envisioning, designing, developing and implementing AI solutions associated with enhancing customerexperience, back office automation and risk and compliance for many Fortune 100 organizations. She has worked in senior positions at Carnegie Group, Inc, an AI startup, Accenture, KPMG, and IBM. Neena has three masters degrees including MBA from leading USuniversities. She is Master certified integration architect from IBM and Open Group as well as certified Project management professional (PMP) from Project management institute. She is also certified in many Cloud and Cognitive technologies. She has widely presented and published many papers in AAAI, IEEE, WCF, ECF, IBM Information on Demand, IBM Insight, World of Watson, IBM DeveloperWorks and various academic journals.