In today’s era of Information, ‘Data’ is the new driving force, provided we know how to extract relevant ‘Intelligence’. This course starts with the core principles of Data Science, and then equips you with the basic tool and techniques of data handling, exploratory data analysis, data visualization, data-based inference, and data-focussed communication. The course will also introduce you to the fundamentals of Artificial Intelligence – state space representation, uninformed search, and reinforcement learning. Python is the language of choice to introduce hands-on computational techniques. For more details, refer to Introduction-to-DSAI

Aims

The course aims to motivate you to work closely with data and make data-driven decisions in your field of study. The course will also touch upon ethical issues in Data Science and Artificial Intelligence, and motivate you to explore the cutting-edge applications related to Big Data, Neural Networks and Deep Learning.

Intended Learning Outcomes

By the end of this course, students are expected to be able to:

1. identify and define data-oriented problems and data-driven decisions in real life.
2. discuss and illustrate the problems in terms of data exploration and visualization.
3. apply basic machine learning tools to extract inferential information from the data.
4. compose an engaging “data-story” to communicate the problem and the inference.
5. outline the roles and requirements of artificial intelligence in practical applications.
6. discuss and explain fundamentals of state space search and reinforcement learning.

TA Duration

Taught the course for 2 years/4 semesters from Jan-2020 to Dec-2021.