Nandakishor Desai

October 8, 2020 | Thursday | 5 PM

ABSTRACT

Data Analytics Workshop

The internet has revolutionized the world leading to an age of connectivity. It has pushed the boundaries of machine intelligence by enabling sophisticated computing algorithms to be developed and imparting them the ability to efficiently harness large data aggregations. The ability to understand the data and analyzing it effectively through computer algorithms is increasingly becoming an essential skill irrespective of one’s profession. Data analytics has significantly altered social dynamics and world order. It is imperative that students and young professionals understand its importance and impact on the positive influences as well as the drawbacks. Further, with advances in data science, artificial intelligence, and machine learning, algorithmic programming has become a necessity for all engineers to tackle different social issues.  This workshop aims at introducing the participants into the field of advanced data analytics with python and building their expertise in the development of a variety of data management strategies and applications.

Workshop Session-1: Fundamentals of Data Handling

In Session 1 of the workshop series, the basic concepts of python for data science will be discussed. The topics include the importance of python in data analysis, python data structures (containers such as lists, sets, dictionaries and arrays), a brief overview of important libraries for data handling (such as NumPy, SciPy, Matplotlib, Pandas, Scikit-learn) and a detailed introduction to NumPy. Some practice programs will be discussed along with introducing the participants to hands-on programming on the discussed topics.

BIOGRAPHY

Nandakishor Desai completed his PhD from the electrical and electronic engineering department at the University of Melbourne. His research focuses on biomedical image analytics involving the development of novel artificial intelligence solutions and decision support systems for diagnostic assistance. He has also worked on a range of data analytics projects exploring the application of machine learning and related technologies to different fields and applications.

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