Core Specialisation
Module: Machine Learning Analytics
No of Credits: 3
Machine Learning is a first-class ticket to the most exciting careers in data analysis today. As data sources proliferate along with the computing power to process them, going straight to the data is one of the most straightforward ways to quickly gain insights and make predictions. Machine learning brings together computer science and statistics to harness that predictive power. It’s a must-have skill for all aspiring data analysts and data scientists, or anyone else who wants to wrestle all that raw data into refined trends and predictions. This is a class that will teach you the end-to-end process of investigating data through a machine learning lens. It will teach you how to extract and identify useful features that best represent your data, a few of the most important machine learning algorithms, and how to evaluate the performance of your machine learning algorithms.
Module: Real Time Analytics
No of Credits: 3
This course introduces students to the principles, methodologies, applications and management of real time big data sets. Topics may include real time systems and technologies, big data basics, industry examples of big data, big data technologies, information management, business analytics, real time analytics, security, compliance, auditing and protection of big data, mobile marketplaces, mobile sites, mobile apps, mobile data tracking.
Module: Digital Analytics
No of Credits: 3
In this course we introduce the concept of digital analytics and explores its’ various major components such as web mining, web analytics, Data Visualisation and online Business Performance Measurement in detail. In particularly, we look at the process, contents and context of managerial decision making. This included on how the implementation of Digital Analytics can help in improving management decisions and discuss issues affecting the success of digital analytics.
Module: Business Intelligence
No of Credits: 3
In this course we introduces the concept of business intelligence and explores its’ various major components such as Data Warehousing, Business Analytics and Data Visualisation, Data Mining and Business Performance Management in detail. In particularly, we look at the process, contents and context of managerial decision making. This included on how the implementation of Business Intelligence can help in improving management decision-support effectiveness and discuss issues affecting the success of Business Intelligence.
Module: Business Process Re-Engineering
No of Credits: 3
This course will introduce the aims and scope of learning Business Process Re-engineering (BPR) and also include the basic principles for analysing and improving business methods, procedures and systems in the business organizations. It covers the methodologies and the know-how of business re-engineering. Best practices of BPR from case studies are also introduced.
Module: Enterprise System Architecture
No of Credits: 3
This course builds upon basic programming skill and develops students further, both theoretically and practically, in a commercial direction. It gives students experience in using third and fourth generation languages, with emphasis on building maintainable programs. It also exposes students on building commercialized programs on basic and intermediate programming skill and knowledge, which integrated with dynamic databases. Furthermore, it will profoundly develop students with systematic and structured project management. The course also introduces the programming techniques of developing ERP application. It is built upon advance programming skills and develops students further, both theoretically and practically. The course is divided into several main topics such as list processing, screens, database updates, enhancement and modification and object oriented programming.
Adjunct Lecture
1. PETRONAS
2. MIMOS Bhd
3. Bank Islam
