About this Course

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Learner Career Outcomes

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Shareable Certificate
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Flexible deadlines
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Beginner Level
Approx. 26 hours to complete
English

Skills you will gain

Computational NeuroscienceArtificial Neural NetworkReinforcement LearningBiological Neuron Model

Learner Career Outcomes

18%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 26 hours to complete
English

Offered by

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University of Washington

Syllabus - What you will learn from this course

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Week
1

Week 1

4 hours to complete

Introduction & Basic Neurobiology (Rajesh Rao)

4 hours to complete
6 videos (Total 89 min), 6 readings, 2 quizzes
6 videos
1.2 Computational Neuroscience: Descriptive Models11m
1.3 Computational Neuroscience: Mechanistic and Interpretive Models12m
1.4 The Electrical Personality of Neurons23m
1.5 Making Connections: Synapses20m
1.6 Time to Network: Brain Areas and their Function17m
6 readings
Welcome Message & Course Logistics10m
About the Course Staff10m
Syllabus and Schedule10m
Matlab & Octave Information and Tutorials10m
Python Information and Tutorials10m
Week 1 Lecture Notes10m
2 practice exercises
Matlab/Octave Programming1h
Python Programming1h
Week
2

Week 2

4 hours to complete

What do Neurons Encode? Neural Encoding Models (Adrienne Fairhall)

4 hours to complete
8 videos (Total 167 min), 3 readings, 1 quiz
8 videos
2.2 Neural Encoding: Simple Models12m
2.3 Neural Encoding: Feature Selection22m
2.4 Neural Encoding: Variability23m
Vectors and Functions (by Rich Pang)30m
Convolutions and Linear Systems (by Rich Pang)16m
Change of Basis and PCA (by Rich Pang)18m
Welcome to the Eigenworld! (by Rich Pang)24m
3 readings
Welcome Message10m
Week 2 Lecture Notes and Tutorials10m
IMPORTANT: Quiz Instructions10m
1 practice exercise
Spike Triggered Averages: A Glimpse Into Neural Encoding1h
Week
3

Week 3

3 hours to complete

Extracting Information from Neurons: Neural Decoding (Adrienne Fairhall)

3 hours to complete
6 videos (Total 114 min), 2 readings, 1 quiz
6 videos
3.2 Population Coding and Bayesian Estimation24m
3.3 Reading Minds: Stimulus Reconstruction11m
Fred Rieke on Visual Processing in the Retina14m
Gaussians in One Dimension (by Rich Pang)30m
Probability distributions in 2D and Bayes' Rule (by Rich Pang)13m
2 readings
Welcome Message10m
Week 3 Lecture Notes and Supplementary Material10m
1 practice exercise
Neural Decoding30m
Week
4

Week 4

3 hours to complete

Information Theory & Neural Coding (Adrienne Fairhall)

3 hours to complete
5 videos (Total 98 min), 2 readings, 1 quiz
5 videos
4.2 Calculating Information in Spike Trains17m
4.3 Coding Principles19m
What's up with entropy? (by Rich Pang)25m
Information theory? That's crazy! (by Rich Pang)16m
2 readings
Welcome Message10m
Week 4 Lecture Notes and Supplementary Material10m
1 practice exercise
Information Theory & Neural Coding1h

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