This course will start with the core principles of Data Science, and will equip 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. The course will 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. Python will be the language of choice to introduce hands-on computational techniques.
| AUs | 3.0 AUs |
| Grade Type | |
| Prerequisite | CZ1003, BG2211, CH2107, CV1014, MS1008, MA1008, EE1005, RE1016 |
| Not Available To Programme | |
| Not Available To All Programme With | (Admyr 2011-2017)-Non Direct Entry, (Admyr 2011-2018)-Direct Entry |
| Not Available As BDE/UE To Programme | |
| Not Available As Core To Programme | |
| Not Available As PE To Programme | |
| Mutually Exclusive With | CE4073, CH0494, CV0003, CZ1016, CZ4073, EE0005, MA0218, MS0003, PS0002 |
| Not Offered As BDE | |
| Not Offered As Unrestricted Elective | |
| Exam |
Available Indexes
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 930 | |||||
| 1000 | |||||
| 1030 | |||||
| 1100 | |||||
| 1130 | |||||
| 1200 | |||||
| 1230 | |||||
| 1300 | |||||
| 1330 | |||||
| 1400 | |||||
| 1430 | |||||
| 1500 | |||||
| 1530 | |||||
| 1600 | |||||
| 1630 | |||||
| 1700 | |||||
| 1730 | |||||
| 1800 |