This course intent for students to understand AI basics with reference to product development and AI applications　

This course's intent is for students to understand AI and ML from decision making perspective and building ability in students to apply AI and ML for decision-making and diagnostic applications.

Due to advance in technology, data is abundant, offering insights businesses require. However, large amounts of data may be complex & difficult to use. In business, we must understand how to capture, clean, contextualize, merge, store, access & analyze data to get better understanding of how to capture & merge data forms into database & convert it into knowledge.

Course provides overview of big data, underlying principles of a distributed system & how this forms a database, data pipelines & practices used in businesses, software systems used to handle big data, data security, & data provenance. Tools used to build databases or run data science introduced & students familiarized with information technologies used to manipulate, store & analyze data.

Students will be able to:
?Understand Big Data and its sources
?Identify the stages of the data processing pipeline
?Describe the design of database and its components
?Develop a plan to store big data into databases
?Differentiate between different solutions that are available for handling big data
?Recognize the value of big data and the opportunities it provides to businesses

This course is an undergraduate major course which is highly recommended for students pursuing a specialization in Ditigal Business and Innovation, and Business Economics, in particular to develop a strong background and understanding of the Artificial Intelligence (AI) and Internet of Things (IoT), and to develop creative thinking skills for innovations based on AI and IoT.

Coming soon

Understand Big Data perspective towards mining unstructured data.

Learn various methods of text mining and applications of text mining.

This is an introductory course in the theory and practice of the econometric methods. The main components of the course deal with the economic applications of the linear multiple regression model, identification and structural estimation in simultaneous models, and analysis of economic behavior.

Coming soon.

This course provides you with the fundamental skills and tools needed to understand, evaluate and conduct business research. Business research is vital in the assessment of new business opportunities, decisions for new products, pricing and product design issues, evaluating employees, identifying operational inconsistencies and other relevant business issues. In this course, we will go through the basic research process to understand how to formulate and structure business problems, gather and analyze qualitative and quantitative data, and make effective decisions based on those data. This is a hands-on course and the emphasis will be on practical skills and building depth and confidence in the most commonly used business research tools.　

This course is a first course in applied statistics. It will familiarize you with the basics of statistical thinking, language, and techniques, thus providing you with the needed skills to address questions that have real life consequences and effects. By the end of the course, you will able to organize and summarize empirical data. This course will also teach you how to compute probabilities, making you skillful in the uses of theoretical probability distributions.

This course begins with the development of elementary functions, including their properties and applications. Then, we will cover finite mathematics, which includes mathematics of finance, linear algebra (matrices, linear systems, and linear programming), probability (starting with foundation for probability with a treatment of logic, sets, and counting techniques), application of linear algebra and probability.