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Ericdo1810

Ericdo1810

Java Programming: Solving Problems with Software

Written 3 years ago
This course, rather than teaching you how to write programs in Object-oriented programming paradigm, teaches you how to write simple programs (classes) in Java.

The purpose of this course, I feel, is not to teach me Java specifically (because they do not really touch on the relationships of classes, objects, superclasses, subclasses, interface, inheritance, etc). However, they teach me programming in the Java development environment. In short, the goal is to teach me how to write simple codes and perform basic algorithms in Java.

With this goal, I think the course did well, I am very comfortable with writing codes in Java after the course. The course also had ample practice via programming exercises (practice quizzes). Their assignments are also of good-quality because they do not have many MCQs (which you can usually just tick until you hit the correct one). Rather, they require us to type in our written program's output to answer. Hence, they make sure that we actually did our work, wrote the program, understand whats going on.

The course, and other courses in the specialization, will give you all the basic concepts in Java, except for the Object-oriented programming paradigm. This one is better taught in other courses like the Java specialization offered by UC San Diego.
My rating
Ericdo1810 completed this course, spending 6 hours a week on it and found the course difficulty to be hard.

Introduction to HTML5

Written 3 years ago
The QUALITY of the course instructional style and content: top-notched.

You can feel the passion of the course instructor, Dr. Collene when she discusses about all the necessary knowledge in HTML5, the history of HTML, its evolution and the reasoning behind developing a global standard for web-page content language. Her passion, coupled with the easy-to-understand lecture slides, are what make this course a really good starting ground for beginner.

I would have gone further to say that this course instructional quality may be even better than many on-campus courses. So, 5/5 stars for that.

However, what is lacking in this course is, the quizzes are rather memory-work-based. Though I understand the instructor really worked hard to deliver quality content, I feel like the quizzes can be improved to include simple code-input questions, or code-analysing questions, rather than consisting mainly of memory work MCQs.

The final project is also a good learning opportunity. The design of the project requirement is good. It requires hands-on application of all the basic concepts in HTML5. However, what is lacking is that the final project should have been peer-reviewed instead of being auto-graded (through an auto-grader that doesn't work).

So, the reason why I think this course is only 4/5 is because of the quizzes being too easy and memory-based and the final project grading mechanism being systematic. Overall, must say this is a very good course for beginner. Not for advanced though, advanced people should look to the HTML5 course on edX offered by W3Cx (WWW Consortium).
My rating
Ericdo1810 completed this course, spending 1 hours a week on it and found the course difficulty to be easy.

Introduction to Big Data

Written 3 years ago
Now:

UCSD course team has massively changed the course contents / structures, including changing instructors, videos and all the assessments. This course is now a pretty solid introduction to big data landscape concepts and technology. I'm happy to see the improvement and the learning value that this course has added on in response to the terrible feedbacks it got from its first launch.

1 year ago:

This course is really terrible. I think even a 5th grader can go through the entire course by himself/herself.

Little value, little technical skills taught (rated 1 star back then)
My rating
Ericdo1810 completed this course and found the course difficulty to be easy.

Object Oriented Programming in Java

Written 3 years ago
This course is very rewarding. I'll tell you why

There is only a single project. But that project is so comprehensive it will familiarize you with all the essential concepts and techniques that you will need in Java OOP: inheritance, overloading, communication between classes, interfaces, etc

Very well-designed applet that makes it satisfying for the learner to complete the course.

Quizzes are easy to pass, however, you still need to complete the programming assignments to tackle the quizzes. Other than that, good understanding of concepts are required too.

You'll build an app, not really your own, but 60% - 70% your own. Why? Because the course team has already done the basic 40% for you. That really ensures the app you created is of a certain quality. Yet, it is not overly spoon-feeding til the extent that you feel you haven't created anything.

However, this course doesn't really test you on your coding specifically. The next courses in the specialization (please join! worth it!) will be teaching advanced concepts and test your coding. I'm looking forward to the next courses in this specialization.
My rating
Ericdo1810 completed this course, spending 7 hours a week on it and found the course difficulty to be medium.

Machine Learning Foundations: A Case Study Approach

Written 3 years ago
This course is easily the best introductory course to Machine Learning one can get. Well-designed, beginner-friendly but also rich in content at the same time. There's a pretty nice balance between theory and practice. Basic, foundational machine learning techniques are taught via GraphLab, a Python-based software specialized in analytics. The course instructor is also one of the founders of this great software.

If you are looking for some courses that are more difficult and challenging than Andrew Ng's Machine Learning course, this course is not for you.

We should understand that, this course is designed to hold learners' hands and walk them through understanding the very basic foundation of machine learning. With that objective in mind, this course did really well in familiarizing a complete beginner with all the terminologies and techniques in Machine learning: regression, classification, clustering, etc.

For people who look for complex algorithms and deep understanding of techniques, this course is not meant for them. However, as the instructors promise, the next courses in the specialization will delve deeper into those complex topics. Hence, there's a great deal of excitement to look into this specialization.

So, the theory part has been really beginner-friendly. For the practical, programming part, it's also very digestible. Remember, the target of this course is beginners, so if you're some expert Python user looking to learn some magics. you will be disappointed as there is not much advanced Python techniques here. However, there's some Python basic requirement, as the software they use is based on Python and you will need to know some basic data structures and iterators in Python to have it easy.

About the software Graphlab, some people complain that the course is trying to sell GraphLab. It is not doing so, and it is unfair to label the course as having such a perverse intention. The course instructor made clear that GraphLab is available for free, indefinitely, for academic purpose. Commercial use is forbidden by the license, which is obvious, and reasonable.

Looking forward to the next courses in this specialization, where the instructors promise that the concepts will be more challenging and complex but that also comes with the possibility of building exciting machine learning applications.
My rating
Ericdo1810 completed this course, spending 4 hours a week on it and found the course difficulty to be medium.

Java Programming: Principles of Software Design

Written 3 years ago
This course is a very well-designed course with meaningful projects. As a learner, nothing is more satisfying than being challenged with real-world applications and conquering the difficult projects.

In this course, the instructors take learners through basic concepts of interfaces and abstract classes, as well as introducing learners to Collections class as well as the Comparable interface in Java.

The first project is to filter a large database of earthquake occurrences, sort them out according to multiple criteria. This project familiarizes learners with how to implement interfaces and abstract classes in Java.

The second project is more challenging, implementing a Markov Model to generate random texts in different languages. This project is particularly challenging because not only learners need to persevere through the constructions of many classes and complicated methods, they also need to be very patient because the implementation uses the Random class quite often, and thus, making debugging less predictable. However, it was a very fulfilling experience being able to complete this project. After this project, I can feel comfortable moving on to intermediate Java classes.

The last project, and the most challenging, is the word-N-gram project, which also generates random texts, but to a higher level of sophistication. This is somewhat similar to a rudimentary machine learning problem: feed the program lots of training data (a long long prose like Romeo Juliet), then the machine can generate meaningful texts based on the statistics of words occurrences in the texts.

It is apparent that the Duke Course team has put in enormous effort into creating this course (and other courses in the series). They are challenging and intensive despite the friendly and fun vibe that instructors always give during their video presentations. The learning experience has been very good with all the courses in this specialization.
My rating
Ericdo1810 completed this course, spending 6 hours a week on it and found the course difficulty to be hard.

Algorithmic Toolbox

Written 3 years ago
One of the best Computer Science algorithm courses (and hopefully, entire specialization) on Coursera's new platform. Here's why:

- The course supports programming assignments in multiple languages: C, C++, Python, Java. You can implement your algorithms in all 4 languages and learn all of them. They have automatic grader for all 4 languages.
My rating
Ericdo1810 completed this course, spending 8 hours a week on it and found the course difficulty to be hard.

Data Structures and Performance

Written 3 years ago
This course is very thorough. It will teach you very very properly, the implementation of different data structures using Java, and the implications those different data structures have on your algorithms.

The lectures are extremely engaging! Seriously, the variety of instructors make it very exciting to follow through the flow of the course, which is very rich in content. Each week there is about 2 hours of lectures and practice quizzes. However, they're broken down into 15+ videos. Each video is presented in a very lay-man-friendly and engaging fashion. Trust me, you'll wish your college lecturer lectures like those instructors if you follow this series.

Are lecture videos everything that you will learn from? No, coupled with the very engaging series of videos, are a variety of programming assignments that will ask you to implement simple algorithms and the data structures. You'll create a fun program to rate how readable your essay is. For example, if I take this piece of writing I just wrote and paste it into the program, it will rate me as "moderately easy to read". However, if I take a piece of legal document and paste it into the program, it will rate "very hard to read". I had fun testing out different pieces of writing after implementing the program correctly. And that was just week 1!!!

Week 2, we still use the same program, however, this time, I had to make the program to analyze the texts more efficiently. We wrote methods to actually time the naive algorithm and the efficient algorithm to have a compare and contrast.

Following weeks, we implement more exciting features into the program, this time is to add in spell-check and "next_word_suggestions". Wow, this really make me feel like I'm learning to do something really useful. Why? I always wonder how emails, MSWord suggest spellings and all. Now I actually can implement it, of course, with very proper guidance provided in the programming instructions. It was a great joy succeeding through the programming assignments.

I'm now off to the 3rd course, Advanced Data Structure in Java. But so far, this series has been nothing short of amazing. They really stand out as one of the best Java courses on the Coursera catalog.
My rating
Ericdo1810 completed this course, spending 8 hours a week on it and found the course difficulty to be medium.

Machine Learning for Data Science and Analytics

Written 3 years ago
This course is not about Machine Learning

It is about algorithms, which is nice, they'll familiarise you (by their lectures) with all the most common types of algorithms.

Now, the next question is, do you get to implement the algorithms? THE ANSWER IS NO. You don't have any programming assignments to do. All they give you are pseudo codes.

Now you may ask, what does algorithms have to do with Machine Learning? Well, the link , as presented by this course, is not really clear. Honestly, if you rename this course into 'Introduction to THEORETICAL algorithm', the course meaning will actually be more appropriate.

Now, there's no programming assignments, what are you gonna do for the quizzes? Okay, the answer is: mostly yes, no questions, some trivial sorting questions which you can do with a pencil. That's it, you don't need more than high school math to do them.

Honestly, I don't understand why the course name is Machine Learning while most of the content is about algorithm, and worse, there's no practice for the algorithms also.

Don't pay 99USD, enough said. You'll better off investing in MITx 6.002x, which teach algorithms too, but provide much richer learning experience, for 50USD only.

My rating
Ericdo1810 completed this course.

Statistical Thinking for Data Science and Analytics

Written 3 years ago
Honestly, I took this course out of curiosity. The name of the course is so catchy, I couldn't resist not to enroll.

When I watch the first videos, I was blown away. The videos were so good! They really did a good job conveying the topic of statistics in the context of data science.

Then I go to the quizzes, to my dismay, the quizzes were so ridiculously simple, one can hardly learn anything from it at all. They ask you to read news articles. Come on, anybody who's interested in Data Science, of course has read at least 5 papers about Data Science to know it is the hot field right now.

Then the quizzes in the following weeks were ridiculously simple. I don't even need a college education or even high school education to do them. Maybe if you've learnt basic statistics in junior high, you'll be able to score full marks for all the quizzes.

The last weeks touch on Bayesian Methods, which is nice, at last.

However, I think the course learning is only summed up in the videos + the last weeks.

It was like watching lectures from youtube.

So please don't purchase the cert. It is 99USD. I would recommend you choosing other Data Science courses on edX or Coursera that are offer more rigorous training.
My rating
Ericdo1810 completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.

Comparing Genes, Proteins, and Genomes (Bioinformatics III)

Written 3 years ago
This course is great, and beyond that. I have never seen any MOOC like this one. So challenging, so rigorous, and so satisfying upon completion (which I just did half an hour ago).

You may be turned off by the word "Bio", if you're a CS person. However, what I can say is: you don't need biology in this course, literallly: zero biology knowledge. To me, all the genes and chromosomes and blah blah, they are just alphabets! The real deal, the real big deal in this course, is that learners will struggle, and struggle a lot, to learn, understand, and implement all the algorithms taught. Hence, if you're really into algorithms to better yourself. This course is really one of the great ones out there.

Why do I rated this course Hard? Actually I wanted to rate Very Hard. That was what I felt. However I think because I'm a newbie, that's why it's very hard. I think for many people, this is Hard only. But why hard?

This is the first MOOC ever I have to watch the video lectures multiple times, WITH PEN AND PENCILS to follow the ideas. The algorithms taught were extremely brilliant that sometimes my jaws dropped and I thought to myself: those people are so smart. Watching lectures in this course is like a cycle: Some Curiosity ---> Utter Confusion ---> Rewind ---> Revelation ---> Oh my GOSH they're so smart.

Yes, watching the lectures, is very satisfying for me. Hence, I recommend, if you are not interested in the quizzes or code challenges, watching the lectures will whet your appetite for algorithms.

About grading, this course is not a mickeymouse course with MCQs that you can blindly guess. Contrary to your expectation, this course has a small percentage for quizzes.

The bulk of the work is the hands-on, practical assignments.

To the people who are not confident in programming, there's a Biology application track, in which you can earn the normal certificate. However, for people who are in for the ultimate challenge of this course, there is the Hacker Track. This is where the course greatness shines.

In total, this course has 20+ coding challenges in which you will implement the various algorithms taught in the course. Well, you don't have to know the biology, but you'll need lots of coding skills in this track. They are hard. All of them are graded by submission of data output. Hence, your algorithm needs to produce exactly the same output as the grader, matching in both values and format. Of course, if you can match the value, matching format is kinda a trivial nuisance.

I gotta say the implementation of the algorithms has been extremely satisfying, especially for a person who is interested in doing data crunching and all, the algorithms taught were extremely relevant. They are hard, expect about 2+ hours on each coding challenge, and 40+ hours overall. However, if you're an algorithm god, maybe you'll do much faster than that. That said, I derive the pleasure from overcoming the challenges. Hence, the course is great, just by its virtue of being tough, alone. Having overcomed those code challenges, I still feel a great need to consolidate them.

This series is a gem on Coursera. The entire series, not just this (because I just completed part V also). This may not be suitable to many people, so please save yourself the frustration if you're not patient wrestling with complex concepts. However, if you're an algorithm enthusiast, you may find this course a very worthwhile learning journey. The taste of overcoming huge challenges is great.

To quote another person on the forum, after completing the course:

"I agree, these are really high quality courses. I cannot imagine how much time they spent making this stuff. This is in a completely different league than other stuff I've taken on Coursera (data science).

I would highly recommend you to do and finish part IV on Molecular Evolution (I finished it this run). It may not seem like that in the beginning, but about half way through beginning with "Evolutionary trees fights crime" and going into the "Was T.Rex just a big chicken" the course has some amazing stories. I found it by far the most interesting part of the entire series, but it is also quite challenging. "

Nothing worthwhile was ever easy.
My rating
Ericdo1810 completed this course, spending 12 hours a week on it and found the course difficulty to be very hard.

Enabling Technologies for Data Science and Analytics: The Internet of Things

Written 3 years ago
This course and the entire series is just terrible. It is very unclear what they're trying to achieve with this XSeries. In this course, they introduced Internet of Things, but draws no link to Data Science or Analytics. It seems like the word Data Science and Analytics are just there to hook attention.

Yes, the course is about IoT, but please, don't expect anything more than FYI lectures and quizzes that merely test the I in the FYI.

Seriously, they even put a price tag of 99, and advertised that this series is from world-renowned data scientists from Columbia. I have nothing against the institution, but clearly this series is really poorly design with no clear aim and no focus. It's all over the place, not really data science, not really machine learning, not really CS, not really analytics, not really teaching any technical skills.

For those who want to buy the course name and the institution's brand, 99 maybe is justifiable. For those who want the knowledge, no, simply no.
My rating
Ericdo1810 completed this course, spending 2 hours a week on it and found the course difficulty to be very easy.

Fast Track Finance #1

Written 3 years ago
I have completed this course partially, just to revise my finance concepts. I can say that this free course is a very rigorous, yet beginner-friendly financial literacy course. This course did the topics of time value of money and risk and returns in finance good justice. Do not expect to be a financial wizard who can make winds on the stock markets after this course. However, if you do complete the course, I'm sure that you'll understand interest rates, compound power of money, what risks are and how returns are related to risks, which are important gate-ways to financial literacy. Of course, you won't be able to learn advanced concepts like risk hedging or how bonds are valued or advanced quantitative methods and other Wall Street stuffs, but you'll know roughly what they mean, and can at least, scratch the surface before diving deeper should you interest go beyond the basics that the course offers. At the very least, you can be more informed when it comes to investing than a random impulsive stock buyer. I highly recommend the introductory financial education that this course offers. It's really finance for everyone.

Prof. Gautam Kaul is really generous. The course is really high quality. Yet, it is free! Really, I was amazed. Finance course, and free? If that is not altruism, I don't know what is!
My rating
Ericdo1810 completed this course, spending 3 hours a week on it and found the course difficulty to be medium.

Critical Perspectives on Management

Written 3 years ago
This course is one of a kind. Never have I seen and experienced such a beautiful blend of history, economics, finance and social sciences so elegantly delivered.

I've done business, economics and finance courses before, both in traditional universities and online, but this course is jaw-dropping unique. The perspectives on management it presents are fresh, powerful and beautifully convincing. Prof. Rolf's teaching was so captivating, I really felt the ideas settling down into my mind with enormous feelings of awe, and before the class, I was expecting dry ideas force-fed down my throats. Basically, his teaching just blew my mind. Beautiful.

The lectures are filmed at high quality (right angles, good amount of light, stable cameras) in a real MBA class, with real MBA students contributing their voices to the already-powerful delivery of Prof. Rolf, the most engaging business professor I've ever came across, both offline and online. It felt so real, it felt so engaging. His delivery was so powerful and his explanation was so lucid I could visualize the entire story in my mind, just by watching him lecturing. More so, the students in the class were real MBA students who actively contributing their thoughtful voices and perspectives. It really felt like I'm attending a real class.

I've had many wonderful MOOC experiences before, but this course, is one of a kind...Just saying it as a great class is a huge understatement. This class, is a wonder of online learning.
My rating
Ericdo1810 completed this course, spending 4 hours a week on it and found the course difficulty to be medium.

Big Data Integration and Processing

Written 3 years ago
I have beta tested this course. As a person who audited the previous versions of this series, I can compare and contrast.

My rating: this is probably the best course in both the new series and the old series. My background? As a data analyst (well, some calls me data scientist) working alongside a big data team, I am familiar with most of the Big data technologies.

When I beta test this course, I was expecting to see only a few technologies covered: for instance, Spark or SQL. To my amazement, this course covers a lot more technologies. The technologies are those that I've heard of, and awesome, there are also several other technologies that are new to me.

Not only it covers the technologies, but it also covers their different uses. For instance, for Spark, the course covers its use in Database, Streaming, Machine learning and Graphing. Wow! Just wow!

Besides the very rigorous coverage of technologies and their underlying concepts, the course also provides hands-on programming assignments, with thorough instructions and gentle difficulty, so that learners can get hands-on with most of the technologies covered. I like the Splunk hands-on and the PySpark hands-on the most. The assignments of those two are classic dashboards and word-counts, applied in the big data context. The programming part is not hard, however, learning and getting accustomed to the interface is a very valuable experience (my big data department uses Splunk by the way, hence, it is very valuable that they teaches Splunk in great details). There are other programming assignments, but I haven't tried them yet as I need to finish this review before going to work. That said, the rigor and thoroughness of this course exceeds my expectation leaps and bounds.

Really, this is the best course in the old and new series. I highly recommend this. Forget about your bad experience with the old series. This course is the new face of this new series.

My rating
Ericdo1810 completed this course, spending 12 hours a week on it and found the course difficulty to be medium.

Inferential Statistics

Written 3 years ago
This course is awesome on so many levels. This is the best inferential statistics course I've come across. Here's why:

- The slides are beautiful and visually appealing, making following the rigorous content easier to digest.

- Instructors are captivating and articulate, the explanations are clear and concise.

- The assignments are very very tough, making the course incredibly challenging, but worth it. This is a huge plus. Without challenge, good statistics understanding won't come.

It was a real challenge getting 100% for everything. For every quiz, I attempted 2 - 3 times to get 100%. The challenge is worth it. I couldn't thank you enough for this course. You explain tough statistical concepts like the difference between prediction intervals and confidence intervals really well. Also, I think this course has the best teaching for Analysis of Variance (I have taken a few other statistics moocs). Also, your course helped me appreciate the meaning of R-squared, standard errors, confidence intervals in a very intuitive fashion. There are many other new things I've learnt from your course, some of them I thought I knew, but you helped me to either "Aha" or understand them more deeply.

Before this course, most of the time statistics to me is like plug-and-play using procedures and and softwares. But now, I can understand the concepts and what the calculations really mean.

I'm grateful to the instructors for creating quizzes that make us really do step-by-step calculations and not just plug data into equations to get results like so many other statistics moocs do.

The pedagogy is really great. Sometimes quizzes can be frustrating because I need to read very carefully into the meaning of the questions and all the options. However, the learning experience is really worth it.

Again, this is an amazing course! This is rare stuff!

It is without a doubt, a lot of passion and effort has been put into this course and this series.
My rating
Ericdo1810 completed this course, spending 4 hours a week on it and found the course difficulty to be hard.

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