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MOOC
Most professions these days require more than general intelligence. They require in addition the ability to collect, analyze and think about data. Personal life is enriched when these same skills are applied to problems in everyday life involving judgment and choice. This course presents basic concepts from statistics, probability, scientific methodology, cognitive psychology and cost-benefit theory and shows how they can be applied to everything from picking one product over another to critiquing media accounts of scientific research. Concepts are defined briefly and breezily and then applied to many examples drawn from business, the media and everyday life.
What kinds of things will you learn? Why it’s usually a mistake to interview people for a job. Why it’s highly unlikely that, if your first meal in a new restaurant is excellent, you will find the next meal to be as good. Why economists regularly walk out of movies and leave restaurant food uneaten. Why getting your picture on the cover of Sports Illustrated usually means your next season is going to be a disappointment. Why you might not have a disease even though you’ve tested positive for it. Why you’re never going to know how coffee affects you unless you conduct an experiment in which you flip a coin to determine whether you will have coffee on a given day. Why it might be a mistake to use an office in a building you own as opposed to having your office in someone else’s building. Why you should never keep a stock that’s going down in hopes that it will go back up and prevent you from losing any of your initial investment. Why it is that a great deal of health information presented in the media is misinformation.
- Keywords:
- Reasoning Problem solving Critical thinking Decision making
- Resource Type:
- MOOC
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MOOC
This Specialization is aimed at preparing students for undergraduate study in an English-speaking university. The course equips you for full participation and engagement with your studies by building awareness and understanding of the core values and expectations of academic culture, and providing you with practical strategies to apply to your studies. In this course, you will learn how to develop your Communication Skills to help you achieve success in your university studies. After completing this course, you will be able to:
1. Recognise the importance of communication in communities of practice at university
2. Understand contexts of communication at university and associated expectations
3. Communicate clearly across a variety of different contexts and to a wide range of audiences by adapting communicative styles appropriately
4. Demonstrate, negotiate, and further understanding through spoken, written, visual, and conversational modes
5. Effectively formulate arguments and communicate research findings through the process of researching, composing, and editing
6. Confidently engage in constructive and critical dialogue with respect and professionalism
- Keywords:
- Communication Interpersonal communication
- Resource Type:
- MOOC
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MOOC
This course gives you easy access to the invaluable learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. We’ll learn about how the brain uses two very different learning modes and how it encapsulates (“chunks”) information. We’ll also cover illusions of learning, memory techniques, dealing with procrastination, and best practices shown by research to be most effective in helping you master tough subjects.
Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you’re already an expert, this peep under the mental hood will give you ideas for turbocharging successful learning, including counter-intuitive test-taking tips and insights that will help you make the best use of your time on homework and problem sets. If you’re struggling, you’ll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you’ve ever wanted to become better at anything, this course will help serve as your guide.
- Keywords:
- Study skills Learning
- Resource Type:
- MOOC
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MOOC
Everyone experiences adversity and stress at some level, whether it’s the pressure to perform in school or work, relationship problems, financial difficulties, or simply the number of tasks to do in a short period of time. All stress isn’t bad, but chronic stress can take its toll on our minds, bodies, and behavior. Research has shown that people can learn and use specific resilience skills (such as optimistic thinking, relaxation strategies, choosing one’s attention) and positive routines (good sleep, scheduling in fun, and so on) in order to better manage stress, bounce back quicker after a setback, be more effective in their academic and vocational pursuits, develop stronger relationships with others, be physically and mentally healthy, and be satisfied with their lives overall. In short, resilience is ordinary magic and can be learned. It does not necessarily mean that you have to be born resilient or get lucky in life. The purpose of this course is to teach individuals the science behind becoming a resilient person. Stated simply, resilience is the ability to survive and thrive. Resiliency is not only about your ability to positively adapt in the face of adverse or challenging circumstances (that is, survive), but it is also about learning the positive skills, strategies and routines that enable you to live a happy, fulfilling, and meaningful life (in other words, thrive). This course gives you the permission to take care of yourself in order to effectively manage life stressors and do what matters most in life.
By the end of this course, you will have learned about the knowledge and skills that you can apply in your life now and in the future to be a resilient person.
- Keywords:
- Stress management Resilience (Personality trait)
- Resource Type:
- MOOC
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MOOC
Handling statistical data is an essential part of psychological research. However, many people find the idea of using statistics, and especially statistical software packages, extremely daunting. This free course, Getting started with SPSS, takes a step-by-step approach to statistics software through seven interactive activities. No statistics software is needed.
- Keywords:
- SPSS (Computer file) Statistics -- Computer programs Statistics -- Data processing
- Resource Type:
- MOOC
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MOOC
The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.
It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.
- Course related:
- AAE5103 Artificial Intelligence in Aviation Industry
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence Machine learning
- 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
Operations Research (OR) is a field in which people use mathematical and engineering methods to study optimization problems in Business and Management, Economics, Computer Science, Civil Engineering, Industrial Engineering, etc. This course introduces frameworks and ideas about various types of optimization problems in the business world. In particular, we focus on how to formulate real business problems into mathematical models that can be solved by computers.
- 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
- Keywords:
- Operations research
- Resource Type:
- MOOC
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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:
- LGT6202: Stochastic Models and Decision under Uncertainty, LGT6802 Guided Study in Logistics II, LGT6803: Guided Study in Logistics III, and LGT6801 Guided Study in Logistics I
- Subjects:
- Business Information Technology and Computing, Data Science and Artificial Intelligence
- Keywords:
- Data mining Problem solving Electronic data processing
- Resource Type:
- MOOC
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MOOC
This course covers the fundamentals of advanced fluid mechanics: including its connections to continuum mechanics more broadly, hydrostatics, buoyancy and rigid body accelerations, inviscid flow, and the application of Bernoulli’s theorems, as well as applications of control volume analysis for more complex fluid flow problems of engineering interest. This course features lecture and demo videos, lecture concept checks, practice problems, and extensive problem sets.
This course is the first of a three-course sequence in incompressible fluid mechanics: Advanced Fluid Mechanics: Fundamentals, Advanced Fluid Mechanics: The Navier-Stokes Equations for Viscous Flows, and Advanced Fluid Mechanics: Potential Flows, Lift, Circulation & Boundary Layers. The series is based on material in MIT’s class 2.25 Advanced Fluid Mechanics, one of the most popular first-year graduate classes in MIT’s Mechanical Engineering Department. This series is designed to help people gain the ability to apply the governing equations, the principles of dimensional analysis and scaling theory to develop physically-based, approximate models of complex fluid physics phenomena. People who complete these three consecutive courses will be able to apply their knowledge to analyze and break down complex problems they may encounter in industrial and academic research settings.
`The material is of relevance to engineers and scientists across a wide range of mechanical chemical and process industries who must understand, analyze and optimize flow processes and fluids handling problems. Applications are drawn from hydraulics, aero & hydrodynamics as well as the chemical process industries.
- Subjects:
- Mechanical Engineering
- Keywords:
- Fluid mechanics
- Resource Type:
- MOOC
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