We've improved performance — pages load faster than before →

Historical snapshot — AY2022/2023 Semester 1 · View current offering →
ModsBC2406AY2022/2023 Semester 1

Analytics I Visual Predictive Techniques

AY2022/2023 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.

AUs4.0 AUs
CategoriesCoreMinorsBDE
Not Available To ProgrammeACBS-2ndMaj/Spec(BA) 3, ACBS-2ndMaj/Spec(BA) 4, ACC-2ndMaj/Spec(PFA) 2, BCE 1, BCE 3, BCE 4, BCG 1, BCG 3, BCG 4, BUS(BA) 3
Not Available To All Programme WithYr1
Mutually Exclusive WithBC3404
Exam

Available Indexes

MonTueWedThuFri
830

00693 SEM (1)

0830-1120 Mon

S4-SR13

00697 SEM (5)

0830-1120 Wed

S3-SR4

900
930
1000
1030
1100
1130
1200
1230
1300
1330
1400
1430

00694 SEM (2)

1430-1720 Mon

S4-SR13

00696 SEM (4)

1430-1720 Tue

S4-SR13

00698 SEM (6)

1430-1720 Wed

S4-SR1

00700 SEM (8)

1430-1720 Thu

S3-SR4

00701 SEM (9)

1430-1720 Fri

S3-SR1

1500
1530
1600
1630
1700
1730
1800
1830

00695 SEM (3)

1830-2120 Tue

S3-SR4

00699 SEM (7)

1830-2120 Thu

S3-SR4

1900
1930
2000
2030
2100