
- Teacher: Cengage Unlimited

This course is designed to prepare business managers with both accountancy and business management skills essential in today’s complex business environment. The course’s learning objectives reflect that: modern accounting with the advent of information technology is no longer simply the recording of historical facts but the assembly and management of accounting information and its distribution to both external and internal users; this information facilitates the decision processes necessary to compete in today’s increasingly complex business world and; an accounting information system capable of providing relevant, timely and reliable information must be administered by knowledgeable, competent management skilled in both accountancy and business management.


Business Intelligence has evolved during the last decade from depicting a photograph of the organization, to predict and prescribe in real time for decision making and competitive advantage. Many methodologies rely on the advancements of Artificial Intelligence, Data Mining, Machine Learning and Deep Learning. During this course the participant will comprehend and apply for business purposes, different algorithms used for advanced predictive analytics. Data manipulation and analysis involve the use of languages like R or Python, but with a strong scope on business applications and the generation of value for the business. Additionally, students will use the Data contained in Big repositories (Extract), apply the data analysis to the whole set of data (Transform) and use the information in real time for decision making and execution (Load). This course follows a Problem Based Learning and Case Based Learning structure, with direct presentations from the instructor to clarify the concepts and applications, providing space for the student to learn, participate and innovate.

This course aims to provide a survey of quantitative techniques commonly used to provide insight into business and management decisions. Particularly important, is the understanding of the assumptions and limitations of quantitative techniques and how these techniques can be used to facilitate practical decision-making. Consequently, emphasis would be placed on formulation, model building, and interpretation of results rather than theory. The course is decision and action oriented, not technique and numbers driven hence the role of the computer and application software, and the use of case studies will be emphasized. Topics covered within the sessions include the following: Describing Data: Graphs and Tables, Summary Measures, Probability concepts and Applications, Decision Analysis, Time Series Analysis and Forecasting, Simulation Models and Game Theory applied to business.
- Teacher: Cengage Unlimited


This course provides a general survey of psychology, its theories and main concepts, including the relationship between brain, nervous system and behavior. Other topics introduced in the course include intelligence and memory, personality, and research methods.