Course Description: 

How does Toyota manage its supply chain, Just in Time (JIT)? How does Walmart forecast its demand and plan accordingly to keep the prices low daily? How does Coca-Cola manage its inventory to ensure the vending machine in your apartment always stocks its product? How does Amazon ensure the products sold on their platform adhere to specific quality standards, and how does SpaceX manage its most complex projects? Embark on a practical exploration of the core concepts, strategies, and techniques that drive efficient organizational operations with our course on Operations Management.

This class goes beyond theory to examine the real-world applications of managerial principles crucial for optimizing processes within organizations engaged in producing goods or delivering services. It focuses on the managerial procedures for efficient operations within organizations that produce goods or provide services. The course covers various areas, such as operations strategy, designing processes, capacity planning, establishing facilities, forecasting, scheduling production, managing inventory, ensuring quality, and overseeing projects. These subjects are interconnected through a systems approach examining an organization's operations function.

Course Description: 

This course provides foundational skills for exploring unstructured business problems. The course will cover techniques to approach decision-making in a systematic manner, enabling students to become more comfortable in handling tasks or projects that are not initially well defined. Methods will include exercises in brainstorming and iterating as well as the use of more traditional analytical tools (such as spreadsheets and visualization software). The course will offer applications across different functional areas and disciplines. After the course, a student should be able to better understand the types of problems businesses confront and solve, the information available to bring to bear on decisions, and modeling techniques and constructs used to solve them. Throughout, communication of results is emphasized. 

Course Description:

Why do people buy expensive laptops? How do people respond to rising fuel prices? Why do ice cream parlors set their shops beside each other? All these questions involve one common thread, that is make a ‘decision’ whether to buy, to respond, or to choose a location by an individual, a firm, o society as a whole we call them ‘economic agents'. The Study of choices made by these economic agents is called Microeconomics. Economists use the tools of microeconomics to study all aspects of life, ranging from business to the environment, and even to dating and marriage. 

In this course, we will use different concepts such as preferences, demand, supply, prices, incentives, and markets to understand how human choices are influenced by changes in these factors. We will discuss the fundamentals of applied economics of the above-discussed questions and many other real-world examples throughout the course. By the end of the course, you will learn how to think like an ‘economist’ studying the market behavior of consumers and producers.

Course Description:

This course aims to teach the fundamentals of probability theory and statistics useful for economists. In this course, we learn probability theory, various distributions, descriptive statistics, statistical inference, estimation, hypothesis testing, and data analysis. These tools are necessary for becoming a good practitioner and consumer of empirical economics. 

The learning objectives of this course are designed according to the first 3 stages of Bloom's taxonomy that is remembering, understanding, and applying. The following goals will be achieved at the end of the course: 

• Understanding statistics as science and learning fundamental elements of statistics

• Implement properties of discrete and continuous distributions of the random variable

• Understanding the relationship between the population parameter and sample estimator

• List desirable finite sample and asymptotic properties for estimators

• Decision-making by drawing statistical inference from point estimates and interval estimates with an empirical project