Master in Business Analytics

 

COURSE DESCRIPTION

MAN201 Statistical Analysis and Fundamentals of Analytics
Course Description This course introduces mathematical statistics, summary statistics and statistical inference, histograms and sample statistics. Probability and probability distributions. Detailed coverage of Gaussian (normal) distribution and the lognormal distribution. Sampling distributions and tests of significance. Analysis of variance. Multiple variables with emphasis on the bivariate case. Correlation and regression. Bayes' theorem and introduction to Bayesian statistics. Gy's sampling theory for the sampling of particulate materials.
Course Contents What is Analytics, History of Analytics, Inferential Statistics, Estimation, Hypothesis Testing, Correlation, Regression Analysis
MAN202 Programming 1: Introduction to Analytical Tools
Course Description This course introduces various programming tools used for analytics.  It covers the fundamentals of a Structured Query Language (SQL) and basic programming concepts, structure, and constructs.  This course also introduces Analytical tools using the menu-driven tasks in SAS Enterprise Guide, the point-and-click interface to SAS, to create queries and reports.  This course introduces other Analytical software.
Course Contents Statistical Programming using Python, R Language, MATLAB, Analytical Tools using SAS, and SAP BI
MAN203 Programming II: Application of Analytics
Course Description This course starts by giving an overview of the steps involved when working out an analytics project in a practical business setting. After discussing the key data pre-processing activities, this course elaborates on how you can efficiently use and deploy both predictive and descriptive state-of-the-art analytics to optimize and streamline your strategic business processes such as marketing campaigns and/or risk management. Examples of business applications that are covered include credit scoring and risk modelling, customer retention and response modelling, market basket analysis and cross-selling, customer lifetime value modelling, and Web intelligence and social network analytics. Students receive extensive practical advice and guidelines on how to put all the analytical tools and concepts to work in a real-life setting. The class focuses on analytical concepts, techniques, and methodologies and their applications.
Course Contents Data Visualization, Business Objects, Dashboarding, Credit Scoring Risk Modelling, Customer Retention, Response Modelling, Market Basket Analysis, Cross-selling, CLV Modelling, Web Intelligence, Social Network Analysis
MAN204 Data Analysis and Design
Course Description This course introduces the data analytics life cycle. It critically analyses methods of dealing with both internal and external data available to organisations. This includes data sourced from cloud and social networks. Effective data usage must take into account efficient data storage and retrieval methodologies to realise potential organisational benefits. Students will apply data modelling techniques and data design strategies to complex problems to illustrate how to maximise the efficient storage and retrieval of organisational data.
Course Contents Levels of Analytics, Analytics Lifecycle, Data Visualization, Statistical Analysis, Forecasting, Predictive Modelling, Optimization
MAN205 Data Integration and Warehousing
Course Description This course gives an introduction to methods and theory for development of data warehouses and data integration. Data quality and methods and techniques for pre-processing of data. Modelling and design of data warehouses.
Course Contents Big Data Querying and Reporting, Data Access and Management, Data Cleaning, Geospatial Data, Relational Databases and Warehouses
MAN206 Predictive Modelling and Machine Learning
Course Description This course introduces concepts in predictive analytics, also called predictive modelling, the most prevalent form of data mining. This course covers the two core paradigms that account for most business applications of predictive modelling: classification and prediction.
Course Contents Data Mining (Supervised and Unsupervised Learning) such as Decision Trees, Clustering, Time Series and Forecasting, Survival Analysis, Risk Analytics, Financial Analytics, Text Mining, Advanced Exploratory Analysis and Outliers
MAN207 Prescriptive Analytics
Course Description This course will focus on how optimization modelling techniques can be used to make the best decisions in a variety of business analytics applications. The emphasis will be on the formulation of different optimization problems and the use of the correct quantitative techniques to solve these problems.
Course Contents Linear Programming, Multi-objective programming, Multi-criteria decision making (MCDM), Large Scale Linear Programming
MAN208 Professional Issues and Social Concerns
Course Description The course introduces ethics and ethical theories; provides discussions on the ethical dilemmas and issues facing IT practitioners. An appreciation and discussion of the Code of Ethics of I.T. Professionals; cyber crimes and appropriate Philippine Laws are also included.
Course Contents Data privacy and security, ethical, moral and legal issues
MAN209 Strategic Management
Course Description This course introduces the key concepts, tools, and principles of strategy formulation and competitive analysis. It is concerned with managerial decisions and actions that affect the performance and survival of business enterprises. The course is focused on the information, analyses, organizational processes, and skills and business judgment managers must use to devise strategies, position their businesses, define firm boundaries and maximize long-term profits in the face of uncertainty and competition.
Course Contents Strategic Management and Leadership, External Analysis, Internal Analysis and Business level Strategies, Anticipating Competitions and Cooperative Dynamics, International Strategy, Organizational Structure and Controls, Corporate Governance, and Strategic Entrepreneurship
MAN210 Special Topics in Business Analytics
Course Description This course provides venue for students to be coached by industry experts on the application of analytics using emerging technologies in each phase of data analytics life cycle. Also, this course provides the students to learn best practices of industry practitioners to real-life application of analytics in a particular area or organization.
Course Contents Coaching from industry experts, plenary sessions from invited industry experts.
MAN299 Practicum 1
Course Description Students will be immersed to partner companies a minimum of 240 hours. The sponsor company will provide current business problems and data for the students to look for possible solutions. Students analyze data and prepare proposal for finding solution.
MAN299-1 Practicum 2
Course Description In this course the student will present the final output of their project to the institution and to the sponsoring company.