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MOOC
Design thinking has become very popular recently. It is because many people believe that design thinking can help generate innovative solutions. Many business and non-business organizations are adopting it to resolving their problems. Even business schools and other disciplines include design thinking in their curriculum. Then, what is design thinking, really? And how can it benefit us?
Design thinking is commonly recognized as a problem-solving process that includes five stages - Empathize, Define, Ideate, Prototype and Test. However, when we compare the design thinking process with the conventional problem-solving process, there are no major differences, except the implementation part. Design thinking looks at problems with a holistic and human-centric perspective. It also tackles complex problems by using a non-linear approach. However, some people claim that considering design thinking as a problem-solving process is too simplistic.
Actually, design thinking should be considered as behaviors and attitudes when dealing with problems. Design thinkers use different thinking styles and attitudes when approaching problems. Design thinkers possess certain personal traits like human-centeredness, having a flexible and creative thinking style, being comfortable with subjective and intuitive judgement, and high self-efficacy. These thinking styles and attitudes help not only in problem-solving but also in finding opportunities. In order to be proficient in design thinking, we should not only understand the design Thinking process, but also have to make ourselves become a design thinker.
This MOOC provides you with core knowledge about design thinking and demystifies design thinking as a process for solving complex and wicked problems.
- Keywords:
- Creative ability Product design Critical thinking
- Resource Type:
- MOOC
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MOOC
Operations management deals with operational planning and control issues, and is needed in all sectors of the society. One of the challenges to operations manager is how to make use of the available resources in the best way for meeting a certain objective. Quantitative approaches are inevitably needed in tackling many of such problems. Operations Research (OR) deals with problem formulation and application of analytical methods to assist in decision-making of operational problems in planning and control. The techniques of OR are useful quantitative tools to assist operations managers, and has a wide applicability in engineering, manufacturing, construction, financial and various service sectors. Operations Research is an applied mathematics subject and is also a course in many engineering and management programmes. This course is designed for both students learning OR and learners who are practitioners in their respective professionals. The mathematical procedures for the OR techniques are introduced in details in the examples provided in the course. This helps learners to master the methodology and the techniques and apply them to achieve their goals through active learning. This course introduces two prominent OR techniques and their extended topics. The Simplex Method for Linear Programming (LP) has been considered one of the top 10 algorithms of the 20th century. LP is an optimization technique for solving problems such as finding the optimal product mix, production plan, and shipment allocation, in order to maximize the profir or minimize the cost. The Critical Path Method (CPM) is a popular technique employed by project managers in scheduling project activities. Some extended topics of CPM are also introduced to deal with certain special situations in project management. In reality, many systems operate under stochastic environment and the operational problems cannot be solved by the known analytical methods. To this end, the simulation approach is introduced in the last chapter of this course. Simulation is a powerful technique for tackling OR problems under such situations.
- Subjects:
- Statistics and Research Methods
- Keywords:
- Operations research
- Resource Type:
- MOOC
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MOOC
This award-winning course aims to sharpen your competitive edge in work and life. It empowers you with positive values and practical problem-solving skills, including creative strategies for addressing challenges from COVID-19. Enriched with interesting animations, a new success story and breakthrough pedagogies, this updated version (2.5) effectively helps you master knowledge and skills requisite for a successful life.
- Keywords:
- Creative thinking Learning ability Critical thinking
- Resource Type:
- MOOC
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Video
Convex Matrix Optimization (MOP) arises in a wide variety of applications. The last three decades have seen dramatic advances in the theory and practice of matrix optimization because of its extremely powerful modeling capability. In particular, semidefinite programming (SP) and its generalizations have been widely used to model problems in applications such as combinatorial and polynomial optimization, covariance matrix estimation, matrix completion and sensor network localization. The first part of the talk will describe the primal-dual interior-point methods (IPMs) implemented in SDPT3 for solving medium scale SP, followed by inexact IPMs (with linear systems solved by iterative solvers) for large scale SDP and discussions on their inherent limitations. The second part will present algorithmic advances for solving large scale SDP based on the proximal-point or augmented Lagrangian framework In particular, we describe the design and implementation of an augmented Lagrangian based method (called SDPNAL+) for solving SDP problems with large number of linear constraints. The last part of the talk will focus on recent advances on using a combination of local search methods and convex lifting to solve low-rank factorization models of SP problems.
Event date: 11/10/2022
Speaker: Prof. Kim-Chuan Toh (National University of Singapore)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex programming Semidefinite programming
- Resource Type:
- Video
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Video
Today's math curriculum is teaching students to expect -- and excel at -- paint-by-numbers classwork, robbing kids of a skill more important than solving problems: formulating them. Dan Meyer shows classroom-tested math exercises that prompt students to stop and think.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Mathematics -- Study teaching
- Resource Type:
- Video
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Others
Being a critical and creative thinker is essential in today’s workplace. It’s also crucial to your career success, regardless of your field or your position. Employers are looking for employees who can creatively problem solve to find answers that are best for both employees and the company.
- Keywords:
- Critical thinking Creative thinking
- Resource Type:
- Others
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Video
Often people make decisions that are not "rational" from a purely economical point of view — meaning that they don't necessarily lead to the best result. Why is that? Are we just bad at dealing with numbers and odds? Or is there a psychological mechanism behind it? Sara Garofalo explains heuristics, problem-solving approaches based on previous experience and intuition rather than analysis.
- Subjects:
- Psychology
- Keywords:
- Decision making
- Resource Type:
- Video
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Video
Learners examine the meaning of theoretical yield, actual yield, and percent yield. They test their knowledge by solving two problems.
- Subjects:
- Chemistry
- Keywords:
- Chemical reactions
- Resource Type:
- Video
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Others
In this interactive object, learners determine the limiting reagent and the excess reagent in chemical reactions. Learners test their knowledge by solving three problems.
- Subjects:
- Chemistry
- Keywords:
- Chemical processes Chemical reactions
- Resource Type:
- Others
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Others
You'll understand how to use a run chart to describe a manufacturing problem.
- Subjects:
- Management
- Keywords:
- Process control Problem solving Production management
- Resource Type:
- Others
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Others
Learners look through a telescope to see what a company chooses to focus on when making decisions about productivity, reducing waste, retraining, solving problems, and motivating employees.
- Subjects:
- Management
- Keywords:
- Organizational effectiveness Organizational change Production management Corporate culture
- Resource Type:
- Others
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Others
The learner will understand how to use brainstorming and a decision matrix to find the best solution to a problem.
- Keywords:
- Problem solving
- Resource Type:
- Others
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Others
Learners examine strategies for evaluating new ideas and accepting change. They consider a list of various reactions to change and a list of actions that enhance teamwork, and check those statements that apply to themselves.
- Keywords:
- Creative thinking Problem solving Critical thinking
- Resource Type:
- Others
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Others
In this interactive object, learners examine the five problem-solving steps of Define, Measure, Analyze, Improve, and Control. Some of the most common measures and tools are listed for each step.
- Subjects:
- Management
- Keywords:
- Production management -- Quality control Process control Six sigma (Quality control stard)
- Resource Type:
- Others
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Others
Students read how the Plan-Do-Check-Act Cycle is used in problem-solving and process improvement. In an interactive exercise, students organize process improvement steps following this model.
- Subjects:
- Management
- Keywords:
- Process control Industrial management
- Resource Type:
- Others
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Others
The learner will explore the techniques used to identify cause-and-effect relationships of a particular problem.
- Subjects:
- Management
- Keywords:
- Root cause analysis Problem solving
- Resource Type:
- Others
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Others
In this learning activity you'll be introduced to the cause and effect diagram.
- Subjects:
- Management
- Keywords:
- Root cause analysis Problem solving
- Resource Type:
- Others
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Others
The learner will identify ways to overcome barriers to critical thinking and problem-solving including false memories, personal biases and prejudices, and physical and emotional hindrances.
- Keywords:
- Critical thinking Critical thinking -- Study teaching
- Resource Type:
- Others
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Others
Continuous improvement programs are sprouting up all over as organizations strive to better themselves and gain an edge. The topic list is long and varied, and sometimes it seems as though a program a month is needed just to keep up. Unfortunately, failed programs far outnumber successes, and improvement rates remain distressingly low. Why? Because most companies have failed to grasp a basic truth. Continuous improvement requires a commitment to learning. How, after all, can an organization improve without first learning something new? Solving a problem, introducing a product, and reengineering a process all require seeing the world in a new light and acting accordingly. In the absence of learning, companies—and individuals—simply repeat old practices. Change remains cosmetic, and improvements are either fortuitous or short-lived.
- Course related:
- MM4311 Strategic Management
- Subjects:
- Management
- Keywords:
- Organizational learning
- Resource Type:
- Others
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MOOC
Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.
This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand.
Accordingly, in this course, you will learn:
- The major steps involved in tackling a data science problem.
- The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment.
- How data scientists think!
- Course related:
- LGT6801 Guided Study in Logistics I, LGT6202: Stochastic Models and Decision under Uncertainty, LGT6802 Guided Study in Logistics II, and LGT6803: Guided Study in Logistics III
- Subjects:
- Business Information Technology and Computing
- Keywords:
- Electronic data processing Data mining Problem solving
- Resource Type:
- MOOC