Graduate-Level Courses at Duke University

Quantum Chemistry (A+)

Quantum Mechanics (A+)

Statistical Mechanics

Solid State/Materials

Models for Complex Materials

Electron Transfer Theory (audit)

Quantum Dynamics (audit)

Computational Biology

Foundations of Nanoscale Science and Technology

Environmental Analytical Chemistry

Graduate-Level Courses at Duke University

Parallel Computing (Grade: A+)

This course is an introduction to parallel programming paradigms. Topics covered include: types of parallelism (task, pipelined/producer-consumer, etc.), programming models (shared memory, message passing, data parallel, etc.), programming environments (OpenMP, Cilk, TBB, MPI, CUDA, etc.), parallel hardware, parallel memory systems (coherence and consistency), application scaling, and topics from recent publications on parallel computing.

Click here to see my notes for this course. See the course website here.

Course Project: GPU Optimization for Stencil-Based Hemodynamics Simulation (click here to see our final report). Exploited and analyzed parallelism in the stencil-based computational model of blood flow simulation using GPU. Achieved a speedup up to 20.

Programming, Data Structure & Algorithms in C++ (Grade: A+)

As described in the course page, "This course will bring students up to speed on programming, data structures, and algorithms. C++ is the language of choice in this class because C and C++ are very commonly used by Computer Engineers. The pace of this course is quite aggressive: we cover more material in one semester than most undergraduate curriculums do in two semesters. This pace is required for all Masters students to be "up to speed" for programming in the Spring semester, regardless of the background they came in with. Accordingly, the workload is high, but not impossible. Many students have become proficient programmers, even with no prior background."

With that said, I was really happy I survived this course and got a A+.

Here are my notes/summary for the course: fundamentals/C, C++, data structures and algorithms.

Course Project: "Baby" Command Shell using C++ (click here to see my code on Github). A C++ program package that has the basic Linux shell functions, free of warnings and memory leak, coded defensively.

Mobile App Development (Grade: A+)

As the syllabus says, "By the end of this class you will be an employable app development programmer, assuming you pay attention in class and spend quality time on each of your assignments and project. As always, you will get out of the class what you put into it – my best students have gone on to land jobs in places like Facebook, but they were ones that really focused on becoming a good Mobile Developer." This course focused on app development concepts and practice using Swift in Apple development environment.

Course Project: Athena – An iOS App (click here to see our project final presentations). It is an iOS app using Swift, which helps the users find sport players with matched skill levels and schedule games. Available for download at the Duke App Store.

Online Courses

Learning from Data, offered by Caltech.

As written in the course website, "this is an introductory course in machine learning that covers the basic theory, algorithms, and applications."

I highly recommend this course as it is a "real" course in Caltech that is well in depth and very clear. You could find lecture videos, slides, homework, and exams on the course website, and work at your own pace.

Machine Learning in Python with Scikit-Learn

This is a course available on Youtube that introduces Python scikit-learn library. I found this tutorials handy to quickly learn how to use Python and scikit-learn for simple machine learning problems.

Data Analysis in Python with Pandas

Again, this is a course provided by the same instructor available here on Youtube. You would be able to do quick data analysis in pandas after the course, even if you don't have any background.

HTML, CSS, and JS for Web Developers, on Coursera

How good is the course? Well, look at my personal website here -- I was able to write the whole site from zero after taking the course. See more detailed introduction here on my Github. It's cool to have your own web pages, isn't it?

Click here to see my notes for this course.

Except for taking courses, I also taught myself the knowledge and tools in computer science when needed. I found that we have been trained to be excellent learners after college and graduate school, which I believe is another strength of receiving higher education at top universities.