Program Introduction
The Data Analytics for Business program prepares students to visualize past, present, and future patterns by linking and presenting information in meaningful ways. The area of data analytics offers deeper insight and meaning of data sets for users by telling the story behind the information. This type of detailed and defined information enables graduates to effectively predict trends, understand the needs of customers, as well as make more informed business decisions.
Students will learn a unique blend of theoretical knowledge and advanced applicable skills. Students will also learn large scale data manipulation, how to collect, curate, encode, and store data sets, which can be analyzed and mined in ways that can be reused and repurposed to solve challenges and predict future patterns for business decision making. Students will gain critical thinking skills that demonstrate the ability to use existing and discoverable data to solve business problems.
Admission Requirements
Diploma or degree in a relevant field from a recognized college or university or demonstrated competence through related work.
Laptop Requirements
MINIMUM RECOMMENDED HARDWARE
• Intel I7 or AMD A10 processor or better with chipset that must support virtualization
• 16 GB of RAM
• 1 TB hard drive
• Ethernet Network Card
• Wireless Network Card
• One USB 3.0 port (two preferred)
• 3 Yr comprehensive parts and labour (Recommended)
SOFTWARE REQUIREMENTS
• Windows 10 Professional Edition
EMPLOYMENT OPPORTUNITIES
Graduates may find employment across almost all public or private sectors. Positions within these sectors include data analyst, business analyst, quantitative analyst, digital marketing, project manager, operations analyst, transportation logistics, systems analyst. Those with an entrepreneurial spirit may prefer self-employment opportunities within the field such as data analytics consultants or design of data management solutions.
International Students
The English proficiency requirement is IELTS 6.0 with no band lower than 5.5, or PTE (Pearson Test of English) Level 54, or TOEFL paper-based test (PBT) score of 550, or internet-based test (iBT) score of 78, or computer-based test (CBT) score of 213, Duolingo score of 100.
Courses
Semester 1
| Code | Title | Credits |
| DAB100
|
INTRODUCTION TO DATA ANALYTICS | 3 |
| DAB501
|
BASIC STATISTICS AND EXPLORATORY DATA ANALYSIS | 5 |
| DAB101
|
INTRODUCTION TO ARTIFICIAL INTELLIGENCE | 2 |
| DAB102
|
INFORMATION MANAGEMENT | 3 |
| DAB103
|
ANALYTIC TOOLS AND DECISION MAKING | 5 |
Semester 2
| Code | Title | Credits |
| DAB200
|
MACHINE LEARNING I | 5 |
| DAB201
|
DATA VISUALIZATION AND REPORTING | 4 |
| DAB502
|
ADVANCED STATISTICS FOR DATA ANALYTICS | 5 |
| DAB202
|
IT SERVICE MANAGEMENT | 3 |
| DAB203
|
BUSINESS ANALYTICS AND DECISION MAKING | 4 |
Semester 3
| Code | Title | Credits |
| DAB300
|
MACHINE LEARNING II | 5 |
| DAB301
|
PROJECT MANAGEMENT ANALYTICS | 4 |
| DAB302
|
ETHICS FOR ANALYTICS | 2 |
| DAB303
|
MARKETING ANALYTICS | 5 |
| DAB304
|
HEALTHCARE ANALYTICS | 5 |
Semester 4
| Code | Title | Credits |
| DAB400
|
SUPPLY CHAIN ANALYTICS | 5 |
| DAB401
|
FINANCIAL ANALYTICS | 5 |
| DAB402
|
CAPSTONE PROJECT | 10 |