The Data Analytics track revolves around three main activities: data capture, data analysis, and data exploitation. Data comes in all scales and forms and requires different capture, storage and access techniques. Students will gain the computing skills to develop systems that have the ability to infer meaning from data and allow stakeholders to make decisions based on that meaning. In this track, we will cover subjects that will prepare students for careers in a wide range of data-driven industries that are adopting data science and big data analytics.
Track Requirement
- For Intake Y2019: 50.001, 50.002, 50.003, 50.004, 50.005. 50.034 are mandatory.
- For Intake Y2020 and subsequent batches: 50.001, 50.002, 50.003, 50.004, 50.005 are mandatory.
- Track core subjects and 4 track electives (not any electives) are mandatory.
Track Core Courses
- 50.007 Machine Learning or 40.319 Statistical and Machine Learning (ESD)
- 50.038 Computational Data Science
- 50.043 Database Systems
Track Electives
- Any ISTD electives listed here.
- 01.116 AI for Healthcare (TAE)
- 01.117 Brain-Inspired Computing and its Applications (TAE)
- 40.016 The Analytics Edge (ESD)
- 60.004 Service Design Studio (DAI)
- 60.007 Interaction Design for Cyber-Physical Artifacts (DAI)
Recommended track electives:
- 50.035 Computer Vision
- 50.039 Theory and Practice of Deep Learning
- 50.040 Natural Language Processing
Core courses are not recognised as track electives. If unsure, please check with the pillar.
A student who intends to sign up for courses offered by other pillars is required to inform the ISTD Pillar his/her plan one term ahead.