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Learning How to Learn: Powerful mental tools to help you master tough subjects

Online Free Online Course by  Coursera
Online / Free Online Course

Details

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 the 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.

At a Glance

  • Self-paced online course
  • 4 hours of video, 3 hours of exercises, 3 hours of bonus material
  • Verified Certificate: Available
  • Subtitles: English, Spanish, Portuguese, Ukrainian

Earn your Verified Certificate

Verified Certificates are co-branded by Coursera and University of California, San Diego. They are printable, digitally shareable, and will empower you with a verified document in-hand.  Link your coursework to your identity, and pass every module to earn your Verified Certificate.

Outline

Speaker/s

Instructors

Dr. Barbara Oakley
Professor of Engineering
Industrial & Systems Engineering, Oakland University
University of California, San Diego

Dr. Terrence Sejnowski
Francis Crick Professor at the Salk Institute for Biological Studies
Computational Neurobiology Laboratory
University of California, San Diego
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