/coursera-learning

My lab works on Coursera, all locked with passwords.

coursera-learning

This is a repo for storing my labworks on Coursera, all secured with passwords.

Coursera has an honor code, requesting that you should never make any content of your homework publicly available. So I've locked them up in archives.

It's just for backup, not sharing.

For those who might be interested in starting their own journey in MOOC platforms like Coursera, I have written a memo/guide here.

Coursera Learning Notes by Zhu Li on 2018.4.6.

Finished Courses

Beginning Custom Projects with Raspberry Pi

Organic Solar Cells - Theory and Practice

  • Organization: Technical University of Denmark
  • URL: Organic Solar Cells - Theory and Practice | Coursera
  • Time: July 19, 2024
  • Grade: 100/100
  • Topic: solar cell, material science
  • Review: Another solar cell course from DTU, except that this one is about organic. Unless you have prior backgrounds in chemical engineering and material science, your experience with this course will probably be limited to popular science lectures, which was exactly how I felt. My learning notes are here.

Introduction to Electronics

Linear Circuits 2: AC Analysis

  • Organization: Georgia Institute of Technology
  • URL: Linear Circuits 2: AC Analysis | Coursera
  • Time: June 27, 2024
  • Grade: 100/100
  • Topic: circuit analysis
  • Review: This is the AC part of circuit analysis course from Gatech. Very excellent and good old-fashioned course on circuitry. As usual, my learning notes are here. The second course is actually shorter and easier than the first. If you wish to learn more, it's good to move on to the "Introduction to Electronics" course from Gatech.

Linear Circuits 1: DC Analysis

  • Organization: Georgia Institute of Technology
  • URL: Linear Circuits 1: DC Analysis | Coursera
  • Time: June 18, 2024
  • Grade: 100/100
  • Topic: circuit analysis
  • Review: This is the DC part of circuit analysis course from Gatech. Very excellent and good old-fashioned course on circuitry. As usual, my learning notes are here. The quizzes have some errors that'll never be fixed, but I couldn't care less because I'm auditing and not paying for a certificate. Actually the abundance of practice problems can be both rewarding and tiring, do what you think is worth the time on this course.

Computational Neuroscience

  • Organization: University of Washington
  • URL: Computational Neuroscience | Coursera
  • Time: June 2, 2024
  • Grade: 96.6/100
  • Topic: neuroscience
  • Review: This is a standalone course on computational neuroscience by University of Washington. It's about 40% computation (quite easy) and 60% neuroscience (a bit advanced). You can always trust UW for its reputation and quality. Please enjoy. You'll get some hands-on practice as well. It's fun. As usual, my learning notes are here.

Trustworthy Generative AI

ChatGPT Advanced Data Analysis

Prompt Engineering for ChatGPT

Physics 102 - AC Circuits and Maxwell's Equations

A Complete Reinforcement Learning System (Capstone)

Prediction and Control with Function Approximation

Sample-based Learning Methods

Fundamentals of Reinforcement Learning

  • Organization: University of Alberta
  • URL: Fundamentals of Reinforcement Learning | Coursera
  • Time: March 18, 2024
  • Grade: 100/100
  • Topic: reinforcement learning
  • Review: This is the first course of the Reinforcement Learning Specialization from the University of Alberta. It was almost 4 years ago since I first took the course. So much happened afterwards and life was probably changed forever for me. Guess I just gotta face it and move on. The course is OK, high quality and excellent text book. For the whole specialization, you can expect to get a 101 on reinforcement learning. Will recommend it for a starter. No need to worry about the difficulty of programming assignments, you'll be enjoying a step-by-step guide of RL on Jupyter notebooks.

Physics 102 - Magnetic Fields and Faraday's Law

  • Organization: Rice University
  • URL: Physics 102 - Magnetic Fields and Faraday's Law | Coursera
  • Time: February 2, 2024
  • Grade: 96.0/100
  • Topic: physics
  • Review: This is the third course of the Introduction to Electricity and Magnetism Specialization. Basically it's all about magnetics and a tiny bit of intro into Maxwell's equations. For an electromagnetics course, this one is extremely easy (considering that you usually deal with symmetric cases and simple calculus). Just remember that electromagnetics is super hardcore physics when it's for real. As always, I was 100% happy with what I went through. Notes were taken here. Seriously, it's still a bit challenging to get everything right.

Physics 102 - Electric Potential and DC Circuits

Physics 102 - Electric Charges and Fields

  • Organization: Rice University
  • URL: Physics 102 - Electric Charges and Fields | Coursera
  • Time: January 10, 2024
  • Grade: 89.5/100
  • Topic: physics
  • Review: This is totally college physics class, be ready for some calculus. Don't worry about the difficulty, it's quite moderate. What really amazed me was the way Professor Hafner tried to make this course as interesting as possible. He really did the best and it worked. Enjoy it. This is the first course of the Introduction to Electricity and Magnetism Specialization. Only reminder is that you should be patient with the calculations in the quizzes. None of the problems was too hard, but it sure took some time to work out every detail. Notes were taken here.

Synapses, Neurons and Brains

  • Organization: Hebrew University of Jerusalem
  • URL: Synapses, Neurons and Brains | Coursera
  • Time: December 29, 2023
  • Grade: 100/100
  • Topic: neurobiology
  • Review: TBH, I didn't know what to expect when first started with this course, like a blank sheet of paper. Luckily, I was content with what I got at last, knowledge, inspiration, questions, answers. This course was very thought-provoking and well balanced on technicality and accessibility. The research on human brain is on its long expedition to infinity, let's be patient and persevere. A learning note was taken during the course.

Photovoltaic Systems

  • Organization: Technical University of Denmark
  • URL: Photovoltaic Systems | Coursera
  • Time: December 12, 2023
  • Grade: 97.6/100
  • Topic: solar cell
  • Review: Similar to the previous course, this one is still an introductory course on solar panels from DTU, but in much greater details and with a more extensive coverage. The course materials and lectures are of great quality. Only imperfection is that some of the lectures have corrupted audio that sounds really weird. It would be favorable to have some prior training in electrical engineering (schematics, electronics, freshman physics, etc.) before taking this course.

Introduction to solar cells

  • Organization: Technical University of Denmark
  • URL: Introduction to solar cells | Coursera
  • Time: November 30, 2023
  • Grade: 100/100
  • Topic: solar cell
  • Review: This course is well-justified to its name "introduction". It provides a basic intro into the solar cell industry, including its working mechanism, fabrication and analysis of various key characteristics. The contents are of high quality (at the time of its creation). There are a few downsides, though. The video lectures are really short (compared to the really long reading materials) and many URL links are long broken. It's a 101 course for pure layman, like me. If you have sufficient backgrounds in material science or energy, it's gonna be too easy for you.

Analysis of Algorithms

  • Organization: Princeton University
  • URL: Analysis of Algorithms | Coursera
  • Time: November 1, 2023
  • Grade: 100/100
  • Topic: asymptotic analysis, combinatorics, calculus
  • Review: Don't let the name fool you, this is actually the part 1 of the Analytic Combinatorics course from Princeton, taught by master computer scientist Robert Sedgewick. I tried my best to follow the lectures and solve problems. I'd say that I'm able to handle only 10% ~ 15% of the contents. This course is more than challenging, as some of the problems are still open for SOTA research. If you're look for a great depth in combinatorics, this is the place of "ad infinitum". Mostly it's about combinatorics and generating function, but it helps a lot if know some algebra, calculus, number theory, differential equations, symbolic logic, formal language and basic programming (solving real problems tends to require a mixed skill set). Passing quizzes means nothing literally. It's important that you truly understand generating functions well enough to apply them on real problems. My notes are here, even though they're almost broken.

Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

  • Organization: Ludwig-Maximilians-Universität München
  • URL: Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python | Coursera
  • Time: October 27, 2023
  • Grade: 100/100
  • Topic: numerical method, python
  • Review: Many people are used to MATLAB when dealing with numerical simulations. With python gaining popularity, I tried to find a course that teaches relevant topics with it and found this high quality course from LMU. The topics can be challenging but you're spared from python programming of the entire simulation scripts. Quizzes are much easier (kindly made so) compared to the lectures given. They still take some time with concepts and calculations, though. Trust me, if the jupyter notebooks were graded assignment, this course could've been 10x harder, as the code written were really really elegant, concise, yet sophisticated (a proof of their efforts to prepared this course as best as they could, salute). If I were a newbie, I'd struggle for a long time to make the elastic wave simulation work properly with sufficient accuracy and stability. Numerical method is itself an advanced engineering topic, thus it's hard enough to make it look easy. It would be favorable if you have some prior backgrounds in maths and physics, at least engineering level.

Property and Liability: An Introduction to Law and Economics

  • Organization: Wesleyan University
  • URL: Property and Liability: An Introduction to Law and Economics | Coursera
  • Time: October 18, 2023
  • Grade: 89.4/100
  • Topic: law
  • Review: I was looking for some courses on law and this suited me perfectly. It's centered around property and liability laws, but extended the topics to provide you with a birdview of the US and European legal systems. Lectures are very long with a whole lot of interesting case studies. Quizzes are intensive, so don't expect to pass this course without some patience and efforts. As always, I took some notes to help digest the rich contents of this course.

Numerical Methods for Engineers

  • Organization: The Hong Kong University of Science and Technology
  • URL: Numerical Methods for Engineers | Coursera
  • Time: October 9, 2023
  • Grade: 100/100
  • Topic: math, numerical analysis, matlab
  • Review: This is the fourth course of the Mathematics for Engineers Specialization. It's a combination of numerical analysis, scientific computing and some MATLAB programming. The course is both fun and challenging. Again, it was well-designed (specifically lowered) on difficulty to make sure learners without some backgrounds in math and physics can catch up with some efforts. The course is a followup on differential equations. This is natural because working on them usually depends heavily on numerical methods. I do hope you know a bit of ODEs and PDEs. Please Enjoy.

Vector Calculus for Engineers

  • Organization: The Hong Kong University of Science and Technology
  • URL: Vector Calculus for Engineers | Coursera
  • Time: September 22, 2023
  • Grade: 100/100
  • Topic: math, vector calculus
  • Review: This is the third course of the Mathematics for Engineers Specialization. High quality and adequate difficulty. Vector calculus is actually quite a difficult subject, that's why this course was taught in a way that's accessible enough for STEM (rather than math major) students with standard training in engineering. You'll do revision on some calculus classes and dive a little deeper than you used to at college. The quizzes were very very very easy (compared to whatever way they could have been), just try hard and solve all of them. They were made easy for most learners to be able to pass the course, really.

Cryptography I

  • Organization: Stanford University
  • URL: Cryptography I | Coursera
  • Time: September 17, 2023
  • Grade: 97.5/100
  • Topic: cryptography, information security
  • Review: This is one of the founding course of Coursera from Stanford by Professor Dan Boneh, one of the best courses you can possibly find and one like an urban legend. Part I is about basics of cryptography, whereas the gone-forever part II was supposed to be a continuation on some advanced topics in cryptography. It's a shame that ten years after its release, we can no longer enjoy the second part of this classic course. If you got time and infinite patience, please do try the really challenging programming assignments, among which I only did the first one. (Sorry for the laziness, I'm learning several other courses at the same time.) I took notes on this one, here are the bits and pieces. The computation and coding part are only intensive within the programming assignment. If you're just for the lectures and quizzes, paying close attention (maybe replay videos several times) and make the best of your logic reasoning would be more than sufficient. Please enjoy.

A Law Student's Toolkit

  • Organization: Yale University
  • URL: A Law Student's Toolkit | Coursera
  • Time: September 10, 2023
  • Grade: 99/100
  • Topic: law
  • Review: This is an introductory course in law from Yale. It's basically a very accessible intro into law for non-law majors and preparatory course for law school students who are still in their undergraduate stage. The course content is both concise and condensed, in that you can learn a lot of fresh concepts with clearly explained theories and examples in mere 3 weeks. I took some notes and the result turned out to be worthwhile indeed. Expect some case studies and writing work, since there are in total 6 peer review assignments. Lots of case briefs if you're willing, the reading part is really no pain no gain, worth the efforts.

The Science of the Solar System

  • Organization: California Institute of Technology
  • URL: The Science of the Solar System | Coursera
  • Time: August 26, 2023
  • Grade: 92.3/100
  • Topic: astronomy, geology
  • Review: This is another astronomy class from Caltech taugh by Professor Mike Brown. He's famous for his research work that basically kicked Pluto out of the planet ranking. The course is a bit more focused on astronomy and geology (yeah, you'll see how important it is for astronomers for their daily lives) that explains various aspects of the solar system. The course is very newbie friendly, so you can rest assured that you'll be able to pass without solving equations and doing complex calculations. Compared to The Evolving Universe course, this one is less formula intensive and doesn't concern so much of nuclear physics. Passing the course is the least important of all, just enjoy the knowledge.

DevOps on AWS: Operate and Monitor

DevOps on AWS: Release and Deploy

Architecting Solutions on AWS

  • Organization: Amazon Web Services
  • URL: Architecting Solutions on AWS | Coursera
  • Time: August 8, 2023
  • Grade: 100/100
  • Topic: cloud computing
  • Review: This is the third course of the AWS Fundamentals Specialization. It's a course where you'll act as a solutions architect to design a solution plan for a traditional interactive website project, with proposal details and architecture diagrams as your tools. It's good, practice right to the point and not too much of a hassle.

DevOps on AWS: Code, Build, and Test

The Evolving Universe

  • Organization: California Institute of Technology
  • URL: The Evolving Universe | Coursera
  • Time: August 7, 2023
  • Grade: 95/100
  • Topic: physics, astronomy
  • Review: Well, this is one of the few courses from Caltech you can take on Coursera. It's a popular science lecture about the evolving process of our universe. Since Caltech is one of the most hard-core places in the world, you still need some solid maths and physics (at least advanced engineering level) to enjoy this course at its fullest (which I sure didn't, being just basic STEM level). TBH, the course is already made extremely superficial and introductory to be minimally accessible to the general public. Otherwise you're gonna get thrown off the orbit at the last 30% percent of the materials and wonder WTF is going on here. All quizzes are made optional to let people pass without getting stuck and there's no certificate eligible nor grades received. Just, enjoy. (To think that the people talking and listening in the classroom are literally geniuses, it's totally OK to have some trouble catching up.)

Differential Equations for Engineers

  • Organization: The Hong Kong University of Science and Technology
  • URL: Differential Equations for Engineers | Coursera
  • Time: July 29, 2023
  • Grade: 100/100
  • Topic: math, differential equation
  • Review: This is the second course of the Mathematics for Engineers Specialization. This course is even better than the one I took in college, in that it's taught in a way that is just as solid but much more interesting. With theories, reasoning & proofs and lots of application examples, you really get an idea of differential equations (mostly ODE, a tiny bit of PDE) in terms of where they came from and how they're gonna help you get things done. The practice problems are well-designed and rather "non-trivial", unless you're simply enumerating choices to pass the course. I guess it's OK even if you do, solving every problem with complete reasoning and calculation efforts is quite the challenge. Given the time I can spare, I'm able to finish only about 80% of all practice problems (the rest are guesses and enumerations per se.) A solid background with engineering algebra and calculus is preferred and almost required. You gotta be ready to do some integrals by hand/heart if you wanna solve stuff quickly. One last reminder, don't skip the practice problems as they help a lot, they really do.

Migrating to the AWS Cloud

Matrix Algebra for Engineers

Information Systems Auditing, Controls and Assurance

  • Organization: The Hong Kong University of Science and Technology
  • URL: Information Systems Auditing, Controls and Assurance | Coursera
  • Time: July 18, 2023
  • Grade: 100/100
  • Topic: audit
  • Review: I took the course to learn something about auditing, but it's basically intro on concepts and methodologies. Can't really blame the course after all, as auditing is about hands-on practice on lots of industrial scenarios and projects (which couldn't possibly be delved into in details). Besides the professor's voice is a bit hoarse, along with the accent, making it a bit challenging to make clear of what he said. Course completion is piece of cake, so take it if you'd like a one-day quick lecture on auditing.

AWS Cloud Technical Essentials

  • Organization: Amazon Web Services
  • URL: AWS Cloud Technical Essentials | Coursera
  • Time: July 16, 2023
  • Grade: 100/100
  • Topic: cloud computing
  • Review: This is the first course of the AWS Fundamentals Specialization. The course itself is a hello-world on the usage of AWS cloud platform from the angle of a solution architect to come up with full hosting and deployment solution for a software product. It's easy for IT professionals (and extremely learner-friendly and high quality for newbies) to catch on, but I'd also give it a big thumb-up for making the learning experience so great. That's AWS, number one of enterprise IT service provider and king of cloud computing. I spent a bit time with every lab on a fresh free-tier account. Perfectly up-to-date course materials that works as expected, to every detail. Respect. Don't skip the labs, that's everything about this course. The quizzes are just small talks on concepts.

Fibonacci Numbers and the Golden Ratio

Cryptographic Hash and Integrity Protection

Cryptography and Information Theory

Asymmetric Cryptography and Key Management

Mathematical Foundations for Cryptography

Classical Cryptosystems and Core Concepts

Launching Your Freelancing Business

Making Money as a Freelancer

Plan a Successful Freelancing Business

Protect and Grow Your Freelancing Business

Economics of Money and Banking

  • Organization: Columbia University
  • URL: Economics of Money and Banking | Coursera
  • Time: June 15, 2023
  • Grade: 100/100
  • Topic: finance
  • Review: This is one of the best finance course on Coursera. It's been around since day 1, real classic. The whole course is about making sense of money and banking world without delving into calculus and algebra. Nonetheless, some intermediate level of accounting and micro and macroeconomics training will help you better catch up with Professor Mehrling. The content is really abundant and rewarding, just do it. It's not about crunching numbers, though. If you're looking for some quantitative stuff, go to the financial engineering course instead.

Web3 and Blockchain Leadership for Transformation

Web3 and Blockchain Transformations in Global Supply Chains

Introduction to Blockchain for Global Commerce

Cost Accounting: Decision Making

Cost Accounting: Profit and Loss Calculation

Securing Investment Returns in the Long Run

Portfolio and Risk Management

Meeting Investors' Goals

Finance for Everyone: Debt

Understanding Financial Markets

Finance for Everyone: Value

Finance for Everyone: Markets

Finance for Everyone: Decisions

Fundamentals of Finance

  • Organization: University of Pennsylvania
  • URL: Fundamentals of Finance | Coursera
  • Time: April 9, 2023
  • Grade: 100/100
  • Topic: finance
  • Review: The course has terrible review and rating, and I see why. The lectures and quizzes are actually better than I expected because the professor is highly skilled and knowledgeable. She knows her stuff too well and go through it too fast without well-formed definitions. Thus, it's a bad course for beginners, as it's totally not learner-friendly per se. I'd suggest you try the finance course from University of Geneva instead. Still, the reading notes are very good. Week 5 is a proof that this course was made in a rush. It's supposed to be a full-fledged course called "Introduction to Financial Engineering", as you see a ton of extra reading notes were provided that could've extended the course by another 3-5 weeks of lectures and quizzes. Guess Wharton was just too lazy to make that happen. I got some FE skills already, well, managed just fine.

Basics of Cost Accounting: Product Costing

Protecting Business Innovations via Copyright

Protecting Business Innovations via Patent

Protecting Business Innovations via Strategy

Protecting Business Innovations via Trademark

Supply Chain Sourcing

Supply Chain Planning

Supply Chain Operations

Supply Chain Logistics

  • Organization: Rutgers, The State University of New Jersey
  • URL: Supply Chain Logistics | Coursera
  • Time: March 10, 2023
  • Grade: 98.2/100
  • Topic: logistics
  • Review: This specialization is about logistics and supply chain management. The course is well-designed and both fun and rewarding, with some quizzes and peer-reviewed projects to follow. It's good training on thinking for small business starters. Totally beginner-friendly, so no worry.

Introduction to Corporate Finance

Managing Social and Human Capital

Introduction to Financial Accounting

  • Organization: University of Pennsylvania
  • URL: Introduction to Financial Accounting | Coursera
  • Time: February 27, 2023
  • Grade: 98/100
  • Topic: marketing
  • Review: Accounting is totally boring with lots of rules & memos and a little baby maths, but Professor Bushee tries his best to explain things really well and make the learning experience enjoyable. I'd say this is a course well-taught and beginner-friendly. Nontheless, you should always keep in mind that it is as boring as it is vital for any practitioner in economy or finance industry. Yeah, the first step.

Introduction to Marketing

Cyber Attack Countermeasures

Enterprise and Infrastructure Security

Real-Time Cyber Threat Detection and Mitigation

  • Organization: New York University
  • URL: Real-Time Cyber Threat Detection and Mitigation | Coursera
  • Time: February 10, 2023
  • Grade: 100/100
  • Topic: information security
  • Review: So I get it. The whole specialization is about conceptual introduction. I'm OK with the course positioning but totally not OK with the quiz, which can be really confusing (intentionally) and all about word puzzles.

Introduction to Cyber Attacks

  • Organization: New York University
  • URL: Introduction to Cyber Attacks | Coursera
  • Time: February 4, 2023
  • Grade: 100/100
  • Topic: information security
  • Review: I got my hands full with family matters, so this took me quite a while (extremely slow pace). This is actually a really introductory course on cyber security concepts, which can be finished easily within a day. I'd say it's too "introductory" even by "introduction" standards. The quizzes are also limited to only conceptual stuff and word puzzles. Not very rewarding learning experience, I'm afraid.

Introduction to Logic

  • Organization: Stanford University
  • URL: Introduction to Logic | Coursera
  • Time: December 31, 2022
  • Grade: 70/100
  • Topic: propositional logic, formal language
  • Review: This is a real challenging (mostly on formal logic) and inspiring course from Stanford. It's serious practice with lots of time-consuming and mind-boggling reading and exercises. The course has good tool for formal logic and proof quizzes, but I'd say it's still very challenging due to lack of support and further explanation (an apparent evidence of this MOOC not well-made enough). Some quizzes just need further illustration on the correct answer to ensure better understanding of what's really going on. Also there's basically no video lecture, which proved a big downside for the course. You'll find this course very introductory if you're math major (professionally), but for students like from CS background, you gotta be ready to burn some brain cells for it. Acutally I got stuck on some of the proof quizzes (some I couldn't, some I found buggy) and gave up at last. I just can't afford the indefinite time needed due to my current ongoing career plan. So, I'd cautiously recommend this course to you. Might be a headache, but still worth it for the sake of the training in logical thinking. And, no, I didn't finish the course.

Introduction to Psychology

  • Organization: Yale University
  • URL: Introduction to Psychology | Coursera
  • Time: December 27, 2022
  • Grade: 100/100
  • Topic: psychology, cognition
  • Review: It's been 5 years since I last learned a course. Just for old times' sake. This is a pure introductory course with well-prepared lectures. Still worth the time.

Introduction to Blockchain Technologies

Java Programming: Arrays, Lists, and Structured Data

Java Programming: Solving Problems with Software

Capstone: Retrieving, Processing, and Visualizing Data with Python

Using Databases with Python

Using Python to Access Web Data

Python Data Structures

Programming for Everybody (Getting Started with Python)

Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Advanced Styling with Responsive Design

Interactivity with JavaScript

Introduction to CSS3

Introduction to HTML5

IBM Cloud Private: Deploying Microservices with Kubernetes

IBM Cloud: Deploying Microservices with Kubernetes

Introduction to Augmented Reality and ARCore

Developing and Deploying Microservices with Microclimate

  • Organization: IBM
  • URL: Developing and Deploying Microservices with Microclimate | Coursera
  • Time: September 11, 2019
  • Grade: 99/100
  • Topic: devops, microservice
  • Review: This is the second course of the IBM Microservices Specialization. I'm even less impressed with this one. Some course contents are directly copied from course 1. Is that responsible for students who paid? Besides, it's not difficult to see that the Microclimate product is out of maintenance, as their CICD pipeline docker image doesn't even build. IBM was a great company. Their ideas still are, but their blades already rusty.

Microservices - Fundamentals

Mathematics for Machine Learning: PCA

Mathematics for Machine Learning: Multivariate Calculus

Mathematics for Machine Learning: Linear Algebra

Introduction to User Experience Design

Concurrency in Go

Functions, Methods, and Interfaces in Go

Getting Started with Go

Introduction to Mathematical Thinking

  • Organization: Stanford University
  • URL: Introduction to Mathematical Thinking | Coursera
  • Time: April 26, 2019
  • Grade: 100/100
  • Topic: mathematics
  • Review: This is a rather interesting math course. It's very inspiring and not too tough. Try it if you're still undergraduate-level. If you're already getting a Master or Doctor's degree, it's gonna be too easy for you, thus spoiling the fun.

Machine Learning with Python

  • Organization: IBM
  • URL: Machine Learning with Python | Coursera
  • Time: April 6, 2019
  • Grade: 100/100
  • Topic: python, pandas, scikit-learn
  • Review: This is actually the capstone course for another specialization. Well-organized and user-friendly, I would say. It's basically an sklearn tutorial.

Data Visualization with Python

Data Analysis with Python

Databases and SQL for Data Science

  • Organization: IBM
  • URL: Databases and SQL for Data Science | Coursera
  • Time: March 22, 2019
  • Grade: 100/100
  • Topic: python, sql
  • Review: It's easy, but no longer a no-brainer course. At least it takes you some time to design the sql query. One thing especially terrible about this course is the DB2 Console, just lame. The resource quota allocated for you was just too thin to make it work normally. Apart from this, I would say this course is still well-organized, if only we could do it with MySQL and Jupyter Notebook. It's IBM course after all, what else can I say? I expect better QoS from you, IBM.

Python for Data Science

Data Science Methodology

Open Source tools for Data Science

What is Data Science?

Firm Level Economics: Markets and Allocations

Practical Time Series Analysis

  • Organization: State University of New York
  • URL: Practical Time Series Analysis | Coursera
  • Time: February 15, 2019
  • Grade: 100/100
  • Topic: time series analysis, stochastic process
  • Review: I thought this course was easy, but it turned out to be more mathy than I expected. The things taught here are rather traditional, but can be good training for a data scientist. Neural networks are expressive, but not so intepretable. Better learn some maths to keep your brain from getting so rusty, that you can only rely on superstition of RNG and SGD.It's the way of thinking that's worth the time and efforts. I have a memo here.

Firm Level Economics: Consumer and Producer Behavior

Financial Markets

  • Organization: Yale University
  • URL: Financial Markets | Coursera
  • Time: October 14, 2018
  • Grade: 100/100
  • Topic: economics, finance
  • Review: This is an introductory course in finance. I just want to hear some advice from a Nobel Prize laureate.

The Global Financial Crisis

  • Organization: Yale University
  • URL: The Global Financial Crisis | Coursera
  • Time: September 27, 2018
  • Grade: 100/100
  • Topic: economics, finance
  • Review: This is an in-depth case study course for the global financial crisis. It's accompanied by sufficient quizzes and lectured by Yale professor Andrew Metrick and former Secretary of Treasury Timothy Geithner. Yale quality, don't miss it.

Moralities of Everyday Life

  • Organization: Yale University
  • URL: Moralities of Everyday Life | Coursera
  • Time: September 15, 2018
  • Grade: 100/100
  • Topic: psychology, philosophy, sociology
  • Review: This isn't a course that teaches you anything practical in terms of job-seeking or money-making. It's about more profound questions of human society and existence. If elite universities like Harvard and Yale are deemed as elites, this is the type of education that makes them qualified.

Corporate Finance II: Financing Investments and Managing Risk

Corporate Finance I: Measuring and Promoting Value Creation

Private Equity and Venture Capital

  • Organization: Università Bocconi
  • URL: Private Equity and Venture Capital | Coursera
  • Time: May 12, 2018
  • Grade: 100/100
  • Topic: private equity, venture capital, finance
  • Review: This is an introductory course on private equity and venture capital, without explicit need for background knowledge in finance, economics and accounting. It would be good to learn something like this before you embark on some serious education in finance and investment. It's a good starting point, well worth the time.

Investments II: Lessons and Applications for Investors

Investments I: Fundamentals of Performance Evaluation

  • Organization: University of Illinois Urbana-Champaign
  • URL: Financial Investments I: Fundamentals of Performance Evaluation | Coursera
  • Time: April 29, 2018
  • Grade: 97.1/100
  • Topic: finance, accounting, investment
  • Review: This is the third course of the Financial Management Specialization, a four-module course. Brace yourself because this is a rather intensive one, with extremely long lectures and several peer-reviewed assignments. Don't rush to finish it by skipping the videos and go directly for the homework. I find watching the lectures very rewarding because Professor Weisbenner is a rather funny guy and his lectures share a lot of insights and experiences, which is far more valuable than what you'll get by simply finishing the course. Take the chance to communicate with brilliant minds whenever you have the chance. Homeworks are trivial if you've really devoted yourself to the learnig process and tried to enjoy it, otherwise they'll just be chores and boring to the death. I have a memo for this course on Zhihu.

Financial Accounting: Advanced Topics

  • Organization: University of Illinois Urbana-Champaign
  • URL: Financial Accounting: Advanced Topics | Coursera
  • Time: April 9, 2018
  • Grade: 99/100
  • Topic: finance, accounting
  • Review: This is the second course of the Financial Management Specialization, still a short four-module course, with 4 quizzes and 1 peer-reviewed assignment. The number of participants seemed a bit low, I had no choice but to wait a whole day before getting any response and having my assignment graded. Still, I'm much luckier than the fellows I helped review. They actually waited a week or a month, you believe that? My god. I'm glad I helped them out.

Financial Accounting: Foundations

  • Organization: University of Illinois Urbana-Champaign
  • URL: Financial Accounting: Foundations | Coursera
  • Time: April 7, 2018
  • Grade: 100/100
  • Topic: finance, accounting
  • Review: This is the first course of the Financial Management Specialization, I take this course to learn something about accounting, as a prior knowledge to financial engineering. The peer-reviewed assignment is good, though not enough people are willing to pay to join up, so you don't have as many classmates around the world to share insights with. Still, peer review is a very idea-inspiring process, it's quite different from working on computer programms and expect things to work exactly as you command. You actually seek difference from your own. Investopedia is a good place to drop by. You never get disappointed.

Bitcoin and Cryptocurrency Technologies

  • Organization: Princeton University
  • URL: Bitcoin and Cryptocurrency Technologies | Coursera
  • Time: March 24, 2018
  • Grade: 92.3/100
  • Topic: bitcoin, blockchain, distributed computing
  • Review: I'm glad Princeton presented a course for cryptocurrency for tech professionals. I'd really love to learn some stuff that have great potential for a long-lasting impact in industry, not a tulip bubble or some foolish zero-sum games. That's why I choose to view blockchain and cryptocurrency as two separate ideas, of which the former is of more value to me.

Sequence Models

  • Organization: deeplearning.ai
  • URL: Sequence Models | Coursera
  • Time: February 23, 2018
  • Grade: 100/100
  • Topic: deep learning, natural language processing, black magic
  • Review: This is the last course of the deep learning specialization by Professor Andrew Ng. It's said this one has been postponed for twice already, even this session was three days late for its declared launch date. I can possibly imagine what kind of tight schedule they've been working on to put things together. The course itself is good, but too sloppy. The learning experience is not quite enjoyable for a paid course. I expected better.

Python Data Visualization

Convolutional Neural Networks

  • Organization: deeplearning.ai
  • URL: Convolutional Neural Networks | Coursera
  • Time: January 21, 2018
  • Grade: 100/100
  • Topic: deep learning, alchemy
  • Review: This is the fourth course of the deep learning specialization by Professor Andrew Ng. It's about one of hottest catchphrases, CNN. Convolutional neural network is indeed powerful, in that it's much more effecient and flexible than old-school MLP. Things also begin to get really misty from this point, as you see one magical model after another, without getting any sense where the hell is the explainability. If there's anything that's actually illuminating, it's the feature visualization of CNN and neural style transfer that help you make sense of what every part of a huge CNN can possibly do and what the hidden layers mean.

Structuring Machine Learning Projects

  • Organization: deeplearning.ai
  • URL: Structuring Machine Learning Projects | Coursera
  • Time: January 12, 2018
  • Grade: 100/100
  • Topic: deep learning, alchemy
  • Review: This is the third course of the deep learning specialization by Professor Andrew Ng. It's a two-week lecture on the techniques, rules and inspirations on the strategies to appply when working on deep learning projects. It's basically about rules of thumbs, so don't try to obey everything to the letter and expect things to work like wonder if you do. Think about it, learn from it, reflect upon it. Still, the most valuable part is always the interview with key figures from academia and industry.

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Neural Networks and Deep Learning

  • Organization: deeplearning.ai
  • URL: Neural Networks and Deep Learning | Coursera
  • Time: January 7, 2018
  • Grade: 100/100
  • Topic: deep learning, neural network, python
  • Review: This is the first course of the deep learning specialization by Professor Andrew Ng. It's explicitly made extremely easy because they wish to let AI and Deep learning be known to the general public, not just math/CS/stats professionals. The course is a brief introduction on basic feedforward neural network. If you're a CS major, you're supposed to be able to finish this course within 3 days. Still, the interviews with several leading figures is the greatest part of this course. It is the "sense" from those academic masters that's the most valuable part, which we should try to perceive and follow. The programming assignments are organized as step-by-step tutorials, which take on average within 2 hours to finish.

Probabilistic Graphical Models 1: Representation

  • Organization: Stanford University
  • URL: Probabilistic Graphical Models 1: Representation | Coursera
  • Time: January 4, 2018
  • Grade: 100/100
  • Topic: bayesian inference, markov model, matlab
  • Review: This is the first course of the PGM series, which teaches you some basics of Bayesian inference, Markov network, factor graphs, etc. It's gonna be the building blocks of the bigger picture. If you're not quite familiar with algebra, calculus and probability theory, you're gonna have a hard time doing this. Also, this course is created in 2012, when Python han't risen to power, so you'll have to make do with Matlab. The programming assignments are about 50% reading comprehension, 40% researching and 10% coding. Make sure you take the time to do it by yourself. Cheating only takes ten minutes, and you'll gain nothing from it.

Algorithms Part II

  • Organization: Princeton University
  • URL: Algorithms, Part II | Coursera
  • Time: December 30, 2017
  • Grade: 100/100
  • Topic: data structure, algorithm, Java
  • Review: After being gone for so long, this course is finally back. I don't really expect to learn anything new from it, just for old times' sake. The quizzes are gone, replaced by optional interview problems. The programming assignments are also much easier. If you're new to Computer Science, this is one of the courses you can't miss.

Bayesian Statistics: From Concept to Data Analysis

Applied Text Mining in Python

Applied Machine Learning in Python

  • Organization: University of Michigan
  • URL: Applied Machine Learning in Python | Coursera
  • Time: October 23, 2017
  • Grade: 100/100
  • Topic: machine learning, scikit-learn, pandas, numpy
  • Review: A very well-designed course, teach you to do machine learning by calling all sorts of APIs. Actually, for small to middle-sized datasets, I think this kind of approach is quite handy, or shall we say, "lightweight". For extremely large datasets, small samples can be analyzed with toolkits like this to help make some sense, before we embark on deep learning and system-level optimizations.

Introduction to Programming with MATLAB

Model Thinking

  • Organization: University of Michigan
  • URL: Model Thinking | Coursera
  • Time: October 13, 2017
  • Grade: 100/100
  • Topic: social science
  • Review: An introductory course in social sciences. It's totally for high school students and undergraduate freshmen, with no rigorous math or hands-on case study projects. I guess I'm too old for this.

Microeconomics Principles

Functional Programming in Scala Capstone

  • Organization: École Polytechnique Fédérale de Lausanne
  • URL: Functional Programming in Scala Capstone | Coursera
  • Time: September 3, 2017
  • Grade: 100/100
  • Topic: scala programming, parallel computing, data visualization, spark programming
  • Review: Fifth course of the specialization, a step-by-step guide to a full scale project. The programming is challenging, while not at maths and algorithm, but at parallel programming, memorization, functional programming, all sorts of tweaking to make your code faster and tighter. The grader has a pretty tight memory limit of 1.5GB, which turned out to be a real headache, for you can experience failures randomly, making the programming assignment unnecessarily much harder. Still, every bit of effort pays off. Try it and see for yourself.

Introduction to Data Science in Python

  • Organization: University of Michigan
  • URL: Introduction to Data Science in Python | Coursera
  • Time: August 30, 2017
  • Grade: 100/100
  • Topic: python programming, pandas, data science
  • Review: An introductory course in ipython and pandas. The interactive notebook called "Jupyter" has nice user experience. If you're looking to learn some pandas programming, try it out.

Big Data Analysis with Scala and Spark

  • Organization: École Polytechnique Fédérale de Lausanne
  • URL: Big Data Analysis with Scala and Spark | Coursera
  • Time: August 12, 2017
  • Grade: 100/100
  • Topic: scala programming, parallel computing, spark programming
  • Review: Fourth course of the specialization, relatively short and easy. The programming assignments took me a whole lot of time putting the APIs right. It's something you have to go through when learning a computation framework, no way around. Besides, the lecturer talks rather fast, with 1.5x play speed and no caption, I had the opportunity to practice my listening skill, that's the real fun.

Game Theory

Parallel Programming

Discrete Optimization

  • Organization: University of Melbourne
  • URL: Discrete Optimization | Coursera
  • Time: July 5, 2017
  • Grade: 93/100
  • Topic: combinatorial optimization, meta-heuristics, randomization
  • Review: Very challenging course which requires solid programming skill and lots of paper reading. Given the hands-on experience related to optimization techniques, it's totally worth all the time and efforts.

Functional Program Design in Scala

Functional Programming Principles in Scala

  • Organization: École Polytechnique Fédérale de Lausanne
  • URL: Functional Programming Principles in Scala | Coursera
  • Time: May 10, 2017
  • Grade: 100/100
  • Topic: functional programming, Scala
  • Review: A course to learn Scala as well as functional programming. I'm a freshman for FP, so the programming assignments did give me a little challenge. I guess when one gots so fixed in the mindsets of imperative and objective programming, the adaptation to FP can be rough. I'm gonna finish the whole specialization, as they're all free for now : )

Machine Learning

  • Organization: Stanford University
  • URL: Machine Learning | Coursera
  • Time: April 29, 2017
  • Grade: 100/100
  • Topic: machine learning, Matlab
  • Review: This is one of the "founding courses" of Coursera, thus it is supposed to be easy and interesting (otherwise people would've been scared off in the first place). So it is vital, for every programming assignment, that you try to read and understand the 99% of codes already written for you. The 1% for you to finish is really the trivial part. Otherwise there'll be no gain at all. Also it's fresh experience for those who get to think in a vectorized manner for the first time.

Algorithms Part I

  • Organization: Princeton University
  • URL: Algorithms, Part I | Coursera
  • Time: April 2, 2017
  • Grade: 98.6/100
  • Topic: data structure, algorithm, Java
  • Review: The lecture speed was a bit too slow, so I had to go at between 1.25x and 1.5x speed to save time. Everything is really well explained, making this course very friendly even for fresh beginners. Actually I signed up for this just to do a little practice in Java programming. Considering the ammount of work devoted to the programming assignments, it was a wise decision to join up, well worth the time and efforts.