AY2026 Semester 1 data is now available →
AY2025/2026 Semester 1
Most organizations are data rich and information poor. The large volumes of data in an organization are 'oilfields' rich in information content that are pending extraction with the right tools and models. Analytics involves the art of data exploration, visualization, communication and the science of analyzing large quantities of data in order to discover meaningful patterns and useful insights to support decision-making. The primary objective of this course is to introduce students to various techniques available to extract useful insights from the large volumes of data. At the end of the course, students will not only see the substantial opportunities that exist in real world, but also learn techniques that allow them to exploit these opportunities. This course focus on the use of open source R software, which is one of the key analytics software used in various industries and a critical skillset required in the job market for analytics and data science professionals.
| AUs | 4.0 AUs |
| Categories | CoreMinorsBDE |
| Not Available To Programme | BCE 1, BCG 1 |
| Not Available To All Programme With | Yr1 |
| Mutually Exclusive With | BC3404 |
| Exam |
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 930 | |||||
| 1000 | |||||
| 1030 | |||||
| 1100 | |||||
| 1130 | |||||
| 1200 | |||||
| 1230 | |||||
| 1300 | |||||
| 1330 | |||||
| 1400 | |||||
| 1430 | |||||
| 1500 | |||||
| 1530 | |||||
| 1600 | |||||
| 1630 | |||||
| 1700 | |||||
| 1730 | |||||
| 1800 |
| Mon | Tue | Wed | Thu | Fri | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 830 | 00532 SEM (1) 0830-1120 Mon S4-SR14, ONLINE Wk1-9,11-13, Teaching Wk10 | 00532 SEM (1) 0830-1120 Mon S4-SR14, ONLINE Wk1-9,11-13, Teaching Wk10 | 00536 SEM (5) 0830-1120 Wed S4-SR17, ONLINE Wk1-9,11-13, Teaching Wk10 | 00536 SEM (5) 0830-1120 Wed S4-SR17, ONLINE Wk1-9,11-13, Teaching Wk10 | ||||||||
| 900 | ||||||||||||
| 930 | ||||||||||||
| 1000 | ||||||||||||
| 1030 | ||||||||||||
| 1100 | ||||||||||||
| 1130 | ||||||||||||
| 1200 | ||||||||||||
| 1230 | ||||||||||||
| 1300 | ||||||||||||
| 1330 | ||||||||||||
| 1400 | ||||||||||||
| 1430 | 00533 SEM (2) 1430-1720 Mon S4-SR20, ONLINE Wk1-9,11-13, Teaching Wk10 | 00533 SEM (2) 1430-1720 Mon S4-SR20, ONLINE Wk1-9,11-13, Teaching Wk10 | 00535 SEM (4) 1430-1720 Tue S3-SR3, ONLINE Wk1-9,11-13, Teaching Wk10 | 00535 SEM (4) 1430-1720 Tue S3-SR3, ONLINE Wk1-9,11-13, Teaching Wk10 | 00537 SEM (6) 1430-1720 Wed ABS-SR11, ONLINE Wk1-9,11-13, Teaching Wk10 | 00537 SEM (6) 1430-1720 Wed ABS-SR11, ONLINE Wk1-9,11-13, Teaching Wk10 | 00540 SEM (9) 1430-1720 Wed S3-SR5, ONLINE Wk1-9,11-13, Teaching Wk10 | 00540 SEM (9) 1430-1720 Wed S3-SR5, ONLINE Wk1-9,11-13, Teaching Wk10 | 00539 SEM (8) 1430-1720 Thu ABS-SR11, ONLINE Wk1-9,11-13, Teaching Wk10 | 00539 SEM (8) 1430-1720 Thu ABS-SR11, ONLINE Wk1-9,11-13, Teaching Wk10 | 00541 SEM (10) 1430-1720 Fri ABS-SR8, ONLINE Wk1-9,11-13, Teaching Wk10 | 00541 SEM (10) 1430-1720 Fri ABS-SR8, ONLINE Wk1-9,11-13, Teaching Wk10 |
| 1500 | ||||||||||||
| 1530 | ||||||||||||
| 1600 | ||||||||||||
| 1630 | ||||||||||||
| 1700 | ||||||||||||
| 1730 | ||||||||||||
| 1800 | ||||||||||||
| 1830 | 00534 SEM (3) 1830-2120 Tue S4-SR11, ONLINE Wk1-9,11-13, Teaching Wk10 | 00534 SEM (3) 1830-2120 Tue S4-SR11, ONLINE Wk1-9,11-13, Teaching Wk10 | 00538 SEM (7) 1830-2120 Thu ABS-SR11, ONLINE Wk1-9,11-13, Teaching Wk10 | 00538 SEM (7) 1830-2120 Thu ABS-SR11, ONLINE Wk1-9,11-13, Teaching Wk10 | ||||||||
| 1900 | ||||||||||||
| 1930 | ||||||||||||
| 2000 | ||||||||||||
| 2030 | ||||||||||||
| 2100 | ||||||||||||
