Think Critically: Deductive Reasoning and Mental Models
Master logical reasoning and mental model development for enhanced decision-making and critical analysis.
Master logical reasoning and mental model development for enhanced decision-making and critical analysis.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Critical Thinking: A Brain-Based Guide for the ChatGPT Era Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.8
(2,455 ratings)
Instructors:
English
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What you'll learn
Master deductive reasoning techniques
Develop effective mental models
Analyze complex arguments
Apply logical principles
Enhance decision-making skills
Skills you'll gain
This course includes:
1.1 Hours PreRecorded video
2 assignments
Access on Mobile, Desktop
FullTime access
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There are 2 modules in this course
This course explores deductive reasoning and mental models in critical thinking. Students learn to construct and evaluate arguments, identify logical fallacies, and understand reasoning systems. The curriculum covers classical and modern logic approaches, cognitive science insights, and practical applications.
The Art of Logical Leaps: Mastering Real-World Reasoning
Module 1 · 1 Hours to complete
Navigating the Pitfalls and Potentials of Real-World Reasoning
Module 2 · 1 Hours to complete
Fee Structure
Instructors
Francis Crick Professor at the Salk Institute for Biological Studies
Terrence Sejnowski is a pioneering figure in computational neuroscience, dedicated to uncovering the principles that connect brain activity to behavior. His laboratory employs experimental and modeling techniques to investigate the biophysical properties of synapses and neurons, as well as the population dynamics within large neural networks. He has developed innovative computational models and analytical tools to explore how the brain represents information and how new representations emerge through learning algorithms that modify synaptic strengths.
Computer Scientist and Logician Advances Spatial Logic Research Through Academic Innovation
Adam Trybus is a distinguished computer scientist and logician who completed his doctorate at the University of Manchester, where his research focused on developing axiom systems for spatial logic with convexity. His academic work has contributed significantly to the field of mathematical logic and spatial reasoning. Currently affiliated with the Faculty of Philosophy at Jagiellonian University and Deep Teaching Solutions, Trybus combines his theoretical expertise with practical applications. Beyond his academic work, he has demonstrated entrepreneurial success in the fitness and technology sectors, developing adaptive training methodologies and creating content that bridges theoretical concepts with practical applications. His approach emphasizes the importance of functional fitness and adaptable training systems, as evidenced by his published work "Adaptive Training: Building a Body That's Fit for Function"
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4.8 course rating
2,455 ratings
Frequently asked questions
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