Funny

cool

很好

When it comes to the subject and the learning outcomes, I would rate 5/5. However the methods and the exercises would rate quite lower. Often it's really hard to understand what is wrong with your submissions and the hints given are minimal, so it's not uncommon to be stuck in an exercise for hours not knowing what you're doing wrong. It might be an entry level course but the material is quite demanding if you don't have a programming background. It was the second time I attempted it, the first one was a couple of years ago and I gave up after the first week. This is why I would say that the time required for the completion of this course is wildly understated. Other than that, as a biology graduate I found the skills learned during this course precious. I got hold of some basic Python commands, learned how to implement them to answer questions of biological nature and started thinking a little bit like a programmer. If you have the time and the patience, I would recommend this course.

It's a great course, but as some people pointed out, it's not the most friendly towards beginners. Ate the end of the fourth week the course tells how to install python and to download pycharm. In my opinion these should have been done on the first week. A good tool for code editing make things so much easier that the student can focus more on the code and on the subject matter than trying to find where the got their code wrong. I read a lot of comments in the comment section of people not knowing what they got wrong only to find out that a piece of code was wrongly indented or that they were missing a colon.

Nevertheless, this couser taught me a lot of interesting stuffs. The way we slowly build our methods, solving problems in small steps, and actualy being able to see it being applied to real Dna string like the E_coli genome and the DosR. I thorougly enjoyed this course i'll certainly be back for the specialized ones.

This was an extremely challenging and time-consuming course for me, a non-programmer, non-biologist health care IT professional. My only negative criticism is that for absolute beginners, the estimated time for most exercises is very very very low. Exercises that were estimated at 39 minutes sometimes took me 8 hours of actual labor.

However! Our course instructor, Niema Moshiri was wonderful - very responsive, very patient, and excellent at coaching students without giving away the answers. I learned to read the assignment, then go directly to the comments, reading all of them, and taking especial note of the "instructor replied" answers. I had a good correspondence with a learner for a while - really helped morale and let me feel connected to the community.

And wow! did I learn a lot about the necessity for computational techniques in bioinformatics, and loads about Python programming!

Finally at the end of completing a really tough course.. especially for a non programmer and non statistician .But the point is if i can do so can you..!! At times the course really gets tough and at certain times you can breeze through .! it takes tremendous time and patience to get through it.. The staff especially Mr Neima Moshiri is really helpful. My suggestion for those who want to get through with the course should atleast have some knowledge of python and statistics . Data structures and algorithms.. i had to find my way around quite a lot..!! Just a note while trying to learn python i finished completing codeacademy and sololearn python certification just to finish this course...and stiff feel like a noob in python.. !!!

It's very interesting and informative. I enjoyed learning more about Dna Replication and recall some aspects of python programming.

Although this course claims that you don't need to know how to program, I recommend that you get at least a little more confortable with programming in general before starting this course. It becomes easier that way.

For the authors of this course: I suggest switching the platform Stepik for another one. Stepik is very flawed regarding execution of codes. This leads to a very stressfull and demotivating learning of python.

Overall, this course is pretty good and fun if you would like to expand your knowledge!

I came to this course with a decent computer science background (some undergrad courses) and basically no biology knowledge (grade 10 general science twenty-some years ago). I found this course to be really easy and pretty fun. I'm still quite confused about the biology concepts, but that didn't make it hard to write the code or implement the algorithms. I'm definitely continuing with the following courses. I only watched the first of the videos. It was ok, but I found the interactive text easier better. The only reason I'd watch the videos is to learn the pronunciation of the biology terms, but the prof has a really heavy accent.

This course is both great and a little frustrating.

It's great in that its interactivity gives you a chance to explore the algorithms, and guides you through the development of the algorithms.

It's frustrating in that sometimes the descriptions of the algorithm inputs are ambiguous or (occasionally) misleading. Fortunately, the student discussion is readily available to help you disambiguate the instructions.

Occasionally there are subtleties that go unmentioned.

The programming environment is functional, and, more important, the inputs to programs are available to let you debug the programs in your own environment.

There was some really interesting information covered in this course. However, the programming assignments and explanations seemed unpolished, there were lots of typos or explanations that were simply unclear and confusing, and the randomized algorithm section made it unclear whether I was getting the coding exercises wrong due to a mistake in my coding or whether it was due to the random nature of the algorithm. Having us use a random seed for these algorithms would have cleared things up. Overall, OK introduction to the specialization, but I'm hoping the courses in the specialization will be better prepared.

The course is organized well. The lectures are fantastic. One improvement seriously needed is the grading system. One quiz question asked to normalize probabilities, but it does not specify to what decimal accuracy that we should give the answer. First I gave the answer without rounding. I got "Wrong". Next time I rounded it to two decimal places and I was marked "Right". Why is two decimal places good and the other bad? At least state it in the question please! Such a great course, but suck silly weaknesses makes it look bad, so I hope you take this seriously and correct. Thanks

Initially the course is quite nice and easy to understand, but chapter 4.... Suddenly the pace picks up and you often feel a bit tricked at the examples Especially when the "trial" example is easy and the later test change the input type or require a different access method for an array. From the informatics side, that's a completely unfair way of testing. You can't debug, but the code fails with a strange exception. The forum is "helpful" but usually you see the solution as soon as you open it :( Other than the last chapter, the course was very good though.

it was challenging, but interesting with very exciting code challenges! however, i really wish the theory was explained in a more visual manner. i believe that would increase the understanding of the concepts described there, because as for me, i don't yet feel confident with the theoretical basics of the course. though i got much more confident with python programming - practical part was much easier for me.

anyway, i'm VERY GRATEFUL to the creators of the course for providing me with this awesome opportunity to familiarize myself with Bioinformatics.

Very interesting introduction to two topics at once- genomics and Python programming, resulting in a perfect storm for me! But I thoroughly enjoyed the way the concepts were presented, explained, and then examined in some detail. Perhaps the course stopped too early- just when I was able to build up some momentum. That said, some of the details (especially in the programming exercises) were of uneven difficulty: cleaning up the examples and smoothing the exercises would go a long way to make this course even better.

The stepik interactive text was just amazing !! I think it is a great way to teach. Integrating with Code Academy to learn Python was really helpful. I spent quite a bit of time on a few challenges. However, arriving at the solution was very rewarding. As a biologist, it is a good start for first time exposure to bioinformatics and algorithms. There were some concepts I had to read multiple times to understand. Some detailed explanations by earlier students were helpful in a few cases.

A heavy emphasis on Python using codeacademy's python course. I have been trying to learn python anyway so it complements what I was already doing. I like the integration of biology and tech used. Because I do not know python yet, this is a lot more time and work than other courses I have taken through coursera. I am working through the free version but might restart the paid course to earn the certificate when I am done with the other paid certificate I am working on.

The programming sections of the course are not great. The lack of conventions being followed makes programming become quickly confusing. More mnemonic naming would have prevented hours of going back and forth to check which code snippet exactly is being referenced. The course structure is good and delivers on its title of Bioinformatics for beginners. It is more structured like a case study on how you can use computer science to solve problems of biology.

Good course for trying out some Python programming related to Dna code searches. If you are new to Python, definitely do the complete python training before starting the course. Most exercises have sufficient guidance in the text/lesson combined with hints in the discussion forums. I liked it enough that I am going to try the bioinformatics specialization. This course does not teach how to interface python with other online bioinformatics programs/tools.

The course content is highly challenging and that's great for a sense of accomplishment. The biological problems motivates the biologist to go through the abstract mathematical concepts(but I have to admit there is a threshold where the biologist can not get it well anymore(greedy motifs, gibbs ...) and I wonder if he does really need it to be practical with day to day problems with chip array seq selex...)

be ready you will struggle hard here

This has been a very helpful course, showing me how to program in a fun way because every coding challenge is linked to a biological question. I think the pace of the course was good, without any prior experience in coding I've had a few moments where I was stuck. But thankfully with some patience and helpful replies from the teaching assistant of the course to my questions in the discussion, it was possible to get past those coding problems.

I have some programming background (in R) so I was able to understand much of the code but I definitely would have been lost had I not had any programming experience. And indeed, in the third-party lesson host, many people were commenting on how they were lost. I was able to learn python at a basic level through this course. Definitely not for beginners, however.

The platform makes it difficult to retrieve code from previous lessons (i.e. navigating through lessons in Stepik is tedious and cumbersome). Some of the lessons are not explained very clearly.

However, the course is challenging enough to force you to think and implement solutions. I recommend this for any biologists willing to learn bioinformatics concepts.

I believe the course is kinda too hard for beginners. I had to go through a lot of stress at some points. Perhaps stressing a little bit more on some of the more complex syntaxes would help a lot. That said, I really enjoyed the course and really felt like I learned a lot! I am so grateful for the opportunity of finally getting into bioinformatics.

Very good course that provides a taste on what bioinformatics algorithms look like.

If you are not familiar with Python this will be too difficult for you. Practice python for at least 2 weeks before jumping here.

Explanation for contents in topic 4 can be improved.

Overall it is a great, highly interactive and intellectually challenging course!