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MOOC
Gone are the days when Problem Solving and Decision Making often happened within the four walls of a top boss’s cabin. In the beginning of this century - As we blinked our eyes, the world changed, cabins broke down to give way to open offices, traditional management hierarchy collapsed and saw a horizontal spread. With delegation and authority batons being passed to the executive and trainee levels, Problem Solving and Decision Making skills became a must have quality at all levels in an organization. In simple words it is – have it or leave it.
That’s less said - Just learning the skill of solving problems and taking good decisions isn’t enough. Today, the modern workplace demands the new age executives and managers to expand their potential of creative thinking and bring it to the table while solving problems and making decisions. There is one more news for you, Creativity, Problem Solving and Decision Making skills are no more confined to the management and leadership levels, students who aspire for their dream jobs to be a reality, also will have to bring these skills along with their candidature.
That is why, we decided to offer this practical and highly researched course with all these 3 skills clubbed into 1 course so that you may not have to search anywhere - anymore.
If at any point of your life, you ever felt the need to work upon your creative thinking ability or your problem solving skills or even your decision making capability, look no further, this course is just the right one for you.
- Course related:
- SD5131 Interdisciplinary Project
- Keywords:
- Problem solving Creative thinking Critical thinking
- Resource Type:
- MOOC
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Courseware
This course provides a thorough introduction to the principles and methods of physics for students who have good preparation in physics and mathematics. Emphasis is placed on problem solving and quantitative reasoning. This course covers Newtonian mechanics, special relativity, gravitation, thermodynamics, and waves.
- Course related:
- AP10005 Physics I
- Subjects:
- Physics
- Keywords:
- Physics
- Resource Type:
- Courseware
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Courseware
This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.
- Course related:
- COMP3011 Design and Analysis of Algorithms, COMP1001 Problem Solving Methodology in Information Technology, COMP4434 Artificial Intelligence, and COMP2011 Data Structures
- Subjects:
- Human-Computer Interaction and Computing
- Keywords:
- Computer programming Computer science Python (Computer program language) Artificial intelligence
- Resource Type:
- Courseware
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Courseware
This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include:
A complete set of Lecture Videos by Professor Gilbert Strang.
Summary Notes for all videos along with suggested readings in Prof. Strang’s textbook Linear Algebra.
Problem Solving Videos on every topic taught by an experienced MIT Recitation Instructor.
Problem Sets to do on your own with Solutions to check your answers against when you’re done.
A selection of Java® Demonstrations to illustrate key concepts.
A full set of Exams with Solutions, including review material to help you prepare.
- Course related:
- AMA1120 Basic Mathematics II
- Subjects:
- Mathematics and Statistics
- Keywords:
- Algebras Linear
- Resource Type:
- Courseware
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Others
All resources and notes from the Complete Web Developer in 2022: Zero to Mastery course
- Course related:
- COMP3421 Web Application Design and Development, LGT3109 Introduction to Coding for Business with Python, COMP3211 Software Engineering, and COMP1001 Problem Solving Methodology in Information Technology
- Subjects:
- Computing
- Keywords:
- Web sites -- Design Web site development
- Resource Type:
- Others
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Video
Before the advent of computers around 1950, optimization centered either on small-dimensional problems solved by looking at zeroes of first derivatives and signs of second derivatives, or on infinite-dimensional problems about curves and surfaces. In both cases, "variations" were employed to understand how a local solution might be characterized. Computers changed the picture by opening the possibility of solving large-scale problems involving inequalities, instead of only equations. Inequalities had to be recognized as important because the decisions to be optimized were constrained by the need to respect many upper or lower bounds on their feasibility. A new kind of mathematical analysis, beyond traditional calculus, had to be developed to address these needs. It built first on appealing to the convexity of sets and functions, but went on to amazingly broad and successful concepts of variational geometry, subgradients, subderivatives, and variational convergence beyond just that. This talk will explain these revolutionary developments and why there were essential.
Event date: 1/11/2022
Speaker: Prof. Terry Rockafellar (University of Washington)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Mathematical optimization Computer science -- Mathematics Convex sets Convex functions
- Resource Type:
- Video
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Video
Adaptive computation is of great importance in numerical simulations. The ideas for adaptive computations can be dated back to adaptive finite element methods in 1970s. In this talk, we shall first review some recent development for adaptive methods with some application. Then, we will propose a deep adaptive sampling method for solving PDEs where deep neural networks are utilized to approximate the solutions. In particular, we propose the failure informed PINNs (FI-PINNs), which can adaptively refine the training set with the goal of reducing the failure probability. Compared with the neural network approximation obtained with uniformly distributed collocation points, the proposed algorithms can significantly improve the accuracy, especially for low regularity and high-dimensional problems.
Event date: 18/10/2022
Speaker: Prof. Tao Tang (Beijing Normal University-Hong Kong Baptist University United International College)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Adaptive computing systems Mathematical models Sampling (Statistics) Differential equations Partial -- Numerical solutions
- Resource Type:
- Video
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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