Courses I've taken (MOOC)

As cognitive neuroscience a interdisciplinary subject, we need some other skills and knowledge in order to carry out research in this field such like math and programming etc.

In order to strengthen my programming skills and gain some knowledge about other interdisciplinary subjects(Data Science, Meachine Learning). I took several online courses(MOOCs), mainly in

Moocs I’ve Taken

Courses List

(The courses I’ve taken in school was recorded in my Transcript). MOOCs are listed below.

Introduction to Programming with MATLAB — 07 2015-09 2015

After graduate from high school, I took this course in the up-coming summer vocation in order to improve my programming skills about MATLAB. This course benefit me a lot for my further study and research with MATLAB.



Meachine Learning (By Andrew Ng) — 09 2015-11 2015

I then took this course in the first semester of freshman.

In this course, I got basic understanding about what meachine learning algorithms do.

I realized several algorithms using MATLAB, including Liner Regression, Logestic Regression, Feed Forward Neural Network, SVM, PCA, K-means, Collaborative filtering etc.

After this course, I acquired the ability to running simple meachine learning algorithms using MATLAB. That lay a foundation for my further study about MVPA, Encoding Models and Behavioral Modeling.



Principles of fMRI 1 — 09 2015-11 2015

In spring semester in 2016 , I took this course for gaining some basic understanding about fMRI.

In this course, I studied some basic knowledge about fMRI and fMRI data analyze. Mainly about several points: 1)fMRI Data Structure, 2)Basic MR Physics and imaging, 3)Signal, Noise, and BOLD Physiology,4)fMRI Experiment Design,5)Pre-Processing of fMRI Data,6)GLM univariate analyze and t-contrast

Also, I together with several other friends who is also interested in this field made a Chinese version note of this class for learns in China not good at English. We posted it in Zhihu. Our article has gathered about 260 up-votes and have influenced a lot of people.

Neural Networks for Machine Learning — 10 2016-02 2017

In fall semester in 2016, I took this course for gaining more understanding about meachine learning, particularly about (deep) neural networks.

I learnt about Perceptron, Feed Forward Neural Networ, RBM, Deep Belief Nets, and auto encoders etc. Most importently, I got to know about how to train a deep neural network using unsuperviced learning with pre-trainning processing. I also realized that the learning rules of RBM and DBN share some same point with LTDP in our neural system. This course provide me with not only skills and knowledge about neual network ,also inspire me to do some futher thinking about the relationship between meachine learning and neuroscience.