Master in Information Technology
Data Analytics
| IT251-1 | Data Analytics 1 |
|---|---|
| Course Description | This course deals with automated extraction of hidden predictive information from databases. Data mining has evolved from several areas including: databases, machine learning, algorithms, information retrieval, and statistics. Data warehousing involves data pre-processing, data integration, and providing on-line analytical processing (OLAP) tools for the interactive analysis of multidimensional data, which facilitates effective data mining. This course introduces data warehousing and data mining techniques and their software tools. Topics include: data warehousing, association analysis, classification, clustering, numeric prediction, and selected advanced data mining topics. |
| Credit | 3 units |
| IT252-2 | Data Analytics 2 |
|---|---|
| Course Description | This course introduces the concepts in Statistics and the techniques that can be used to address research and business questions. It discusses how to compute and interpret descriptive statistics, and how to utilize statistical graphs to picture data. This course aims to discuss the inferential methods of estimation and hypothesis testing. Correlation and regression analyses are introduced, and methods for investigating categorical data are presented. The course will also introduce data visualization techniques that will help them understand their data whether structured, semi-structured, or unstructured. Moreover, this will introduce effective principles in order to evade the most common mistakes in visualizing data. |
| Credit | 3 units |
| IT253-3 | Data Analytics 3 |
|---|---|
| Course Description | This course introduces the fundamental concepts in Analytics. It discusses the applications of predictive modelling methods such as decision trees, regression, and neural networks. It also covers segmentation analysis and market basket analysis. Time series analysis is introduced, and methods for modelling and forecasting are presented. The course also covers survival analysis and provides an overview of other analytics techniques that include customer lifetime value and incremental or net-lift modelling. |
| Credit | 3 units |
| IT254-4 | Data Analytics 4 |
|---|---|
| Course Description | This course discusses the set of theories and methodologies of business intelligence that handle large amounts of data and information. This course also covers knowledge management which is the process of capturing, storing, retrieving and distributing the knowledge of the individuals in a business for use by others in the business to improve the quality and/or efficiency of decision making across the firm. This enables the learner to study information tools used to assist decision-makers and describe the process known as decision-making including the three steps involved. |
| Credit | 3 units |
