excellent introduction, which was at an appropriate level for my experience (lots of programming in languages other than python, and just a cursory understanding of genomics).

It was definitely interesting and quite challenging. But in my opinion it is a little hard for beginners. I am glad I did it though. Looking forward to the specialization.

in between the course the continuity breaks and also it jumps to a sudden high level

This is a poor course for Python beginners. There are two things going on here -- CodeAcademy, which has a nicely thought out, clear explanation of basic Python programming. Then there is STEPTIK--the big problem is that the very basic programming instruction in CodeAcademy does provide adequate background to successfully solve the problems in STEPTIK. The STEPTIK section should build on/fill in the gap between what we learned in Python and we need to still learn to complete the problems. Many of the solutions provided in the solutions forum use coding that was not introduced to us in CodeAcademy.

This course may work for computer programmers who want to explore Bioinformatics. After trying twice to complete Week 1, I finally gave up. What's the point if I have to copy solutions from the Solutions forum (that I don't understand) to proceed? I'm glad I did not purchase the course before I tried out Week 1.

This course is rather fun to take!! It slowly builds your knowledge base in Python (mostly through CodeAcademy exercises), while at the same time giving biologically-relevant problems to solve so that you get some practice in applying what you learnt in a real-world context. I would especially recommend it to Life Science-trained people who want to learn how to program in Python, but find themselves put off by the fact that most of the practice problems out there are not very relevant to their field, such as constructing irrelevant programs, for example. In this case, such people are will find themselves at home in the problems given in this course. The familiarity of the context in which the problems exist proves to be quite motivating, and makes the task of trying to find the solution using programming very rewarding. Most of the problems revolve around finding different kinds of patterns in DNA strings, such as finding frequent kmers, finding motifs, etc. But don't worry, you aren't just finding them for the sake of finding them, there is a very real biological question used to frame these pattern-finding problems, which prevents this course from being dry.Just take note though: you must try and complete at least a few units CodeAcademy Python track BEFORE starting the course, instead of starting DURING the course as expected. This is because during the first few days of the course, it can be quite distracting to constantly jump between the course material and CodeAcademy, which might break your link and cause you to lose interest in the problem you are currently trying to solve. Solve some CodeAcademy units first, and then tackle the problem in a more continuous manner.

Great great course ! Many thanks for those who made it possible, as i learned a lot. I am a seasoned programmer in manny languages so i have learnt both Pyhon and genetics. Very happy !

The course was fairly interesting and I had a lot of fun in completing it. The only problem I had with the course was with its python aspect. Apart from that, it was amazing!

Warning: Unless you are experienced with python scripting, this course will NOT be quickly finished. Exercises are solved by typing (or pasting) in your python functions. The website supplies the input variables and runs any additional functions (such as looping your algorithm 1000 times). Often you cannot see the input variables or the additional functions applied, which can make troubleshooting difficult. Typically my first few submissions would be wrong; the code worked on my laptop but not on the website. It was difficult to track down the incompatibility or my error, since I did not know what the website was trying to do.

There are four parts. Part 1 is simple and easy, typically 1-3 functions per exercise. Part 2 starts to combine more functions towards the end. Part 3 and part 4 took me probably about 8-10 hours of work each, with the reported aggregate success rates on several exercises between 10-13%. It wasn't uncommon for people to comment they'd spent days on a single exercise (there are about 10-15 exercises per part). Occassionally someone will post answers to the exercises in the comments, but this is rare. Usually, you're on your own until you figure it out. You can read ahead, but you get no points until you go back and complete missing exercises. Once you complete an exercise, a solution forum opens where you can read how others did it much better than you.

Nevertheless, if you google (constantly!), spend many hours, and ask questions in various fora on the internet, you'll eventually find a solution. Along the way, you should be ready to tear out your hair over your code being repeatedly rejected as wrong. Apparently this latter ritual is also a measure of your quality in bioinformatics, since everyone who works in this field must be prepared to endure the grief of inexplicably failing code, persisting until a solution is found. So the frustration is supposedly part of the learning process.

Ultimately, this is how you will learn what your code is doing. You dive into it with pdb and check everything at every step until you understand the code. It can take a few minutes to an hour, but usually you do this anyways in order to troubleshoot.

Outside of the step-by-step function of your code, the broad goals of what you're doing, the aim of your algorithms and the biology, are mostly well explained. The text frequently invites you to stop and think, which for me meant stop and read others' comments, since some people are very good and post some enlightening commentary, which became part of my education. Every part has a couple optional excursions where you're debriefed on historical or related knowledge, which were actually surpisingly fun to go through. It was nice to read short, interesting sections without the pressure of a looming exercise to cap it off.

There is however no pressure. The exercises are not on a deadline. The quizzes can be repeatedly attempted until you have a 100%, with about half the questions never changing, and the other half typically only changing the numbers. Can't comment on the videos as I never watched a single one, just did the Stepik exercise program.

This course is marketed for beginners, but there's a big caveat with that (hence my 4 stars for that deception).

I began with a warning, so I'll end with a reminder of that warning:

Constructing your coding is not well explained. You're given a goal that's usually clear, but the "how to reach that goal via python" is almost always entirely up to your programming intuition. Your biology knowledge won't help you at this in any way. If you suck at programming / never scripted before, and you're looking to have your hand held through python, then either don't do this course, or maybe make sure you have the recommended codeacademy accompanying course for Python. I didn't do the codeacademy course, so I can't vouch for that, but maybe it will help. I know from others' comments on the exercises and my own experience that this can take over 10 hours for either part 3 or part 4 if you don't know what you're doing, and at times, specifically regarding errors in your code, leave you at a frustratingly complete loss for how to proceed, where you're on your own to figure out how to get your code working.

I really enjoyed the class, however, I have two complaints/recommendations.

1. Much of the content seems geared towards biologist/life science professionals who have a strong grasp on the concepts being presented. I am a software developer with little background in the life sciences, much of what was discussed as it relates to biological processes was new to me. It would have been nice to have had a companion document for the biology side of the course, similar to the Python programming companion.

2. Successfully completing work in Week 4 depends on successfully completing the "GreedyMotifSearch", I didn't search the forum or FAQ too much, but providing more visible support for people who get the correct answer, but exceed the time limit might be useful. I was able to easily identify my problem using a line profiler, but those new to Python may not know "Best Practices" for optimizing code.

Anyway, that's it. Thanks.

Not at all for beginners. A coding background is necessary to make any sense of the material.

It's too difficult as a beginner and introductory course, especially Weeks 3 and 4.

Figure???Figure??? 80% figure were not working??????

An excellent course that is a great opportunity for anyone interested in bioinformatics, no previous experience is necessary but either a biological, mathematical or computing background will give you advantages in certain areas. Being a biologist I struggled at first and many of you may do the same but stick with it, work hard on it and you will be rewarded and it is incredibly satisfying.

Due to the practical coding nature of the course, each week can take up a lot of you time. Best if you have a few weeks free (e.g. a graduate student like me) so you can spend a few whole days of it but could be done before/after work if you are motivated and plug away at it each day - just something to keep in mind though, don't expect a light easy 1 hour a week course, it is intensive but in a good way. It can get frustrating, you will want to give up time and time again....but stick at it and you will have a shiny new Coursera certificate and a wealth of programming knowledge under your belt once you finish!

A massive two thumbs up for this course, one of the best ones out there that gives you real worthwhile skills that employers and academia want. Thanks to all the course staff for a great experience!

Coming from a Computer Science background this course is very interesting and relatable. The coding part is pretty easy, so if you are familiar with any programming language, I think the programming part will be easy for you. I definitely recommend this course to anyone familiar with programming, who is also interested in the bioengineering aspect!

That being said, I like the idea of the course, but I encountered some issues with stepik's online classes/texts.. Their servers seem to be down so I am not even able to complete the interactive text part at the time I want (I keep getting 500).. I was expecting something more reliable especially since this is not free .. But again the idea is cool just wish there were no down times

My major is biotechnology, I have learnt C program before and I quite enjoy programming, but my major courses have nearly nothing to do with programming, which made me worried about the waste of my knowledge. But now, I feel so excited and refreshed, cause I have learnt how to connect both subjects! And I want to say that this course is very clear with beautiful illustrations and has lots of expansion which can lead us to continue further study, though I have a problem that I can't watch the teaching video, what a pity~

And I'll definitely continue the following course: Bioinformatics Specialization!!!

I really enjoyed this course! That's why I will definitely dive into the Bioinformatics Specialization. The presented material is well explained and the coding challenges are increasingly demanding and motivationally designed. Furthermore the instructors are always helpful pointing in the right direction without revealing too much.

Maybe a little advice: If you are completely new to programming or biology (or perhaps both) be prepaed to spend more than 4 h/week because you'll propably need more training time.

The course provides some meaningful questions in biological context (rather than abstact excercises in some textbooks) for you to solve. It is really fulfilling when you put what you learnt into use and made improvements on your code to solve the questions better. The exercises are actually challenging for programming beginners. But if you persist, upon completion of this course you will find youself equipped with some solid knowledge on bioinformatics, which will definitely benefit your future career.

Great Course!! Although I already had a background in Python Programming, I can see how this class could gently eases someone with no knowledge of Python (or programming for that matter), into a Novice Python 3 Programmer. The Biology aspect was also well presented. Difficult concepts were well explained, and extra material was given for topics that were not directly related to solving the challenges at hand, but fun and interesting to learn.

In my opinion, this is a fabulous course and will recommend it for all beginners in bioinformatics. At the beginning of the course i was a complete rookie at python programming and was surprised to find myself able to code comfortably by the end of the course. The course was challenging at some points especially week 4, but i eventually made it. I find it worth all the time i put into this. Big thanks to the course instructors

Great course. I learned a lot. I came into it with only a little bit of background in Python coding. I worked through the recommended Code Academy modules and attempted the course work early and often. I feel like my understanding of algorithms, molecular biology, and Python coding have all improved in just 4 short weeks. I look forward to learning more Python, algorithms, and molecular biology from UC San Diego and others.

A really fun and addictive course with some fascinating biology thrown in. I come from a chemical biology background and I had never done programming before. It's challenging, but it's highly motivating when you do solve something. It makes you become familiar with Python in a way that just the Codecademy course by itself simply won't. Phillip and Pavel, thank you for making this course!

Definitely challenging. If you are new to Python, you will need to do the CodeAcademy course and have a solid grasp of dictionaries, lists, and string manipulation. Even if you do know programming, you will likely spend more time than estimated on each week. I spent probably 8 hours per week. That said, it is extremely rewarding. I highly recommend this.

Personally, I never believed I would enjoy coding, but I had a deep interest for biology. This course not only helped me develop an interest and grasp the basics of programming in python but also gave me an insight as to how I can use this knowledge I gained in various fields such as bioinformatics.

As a Computer Science undergrad that works with Python, I considered the programming tips very begginer-friendly and could easily follow the presented biological knowledge that was required to complete the course. The course certainly made even more interested in Bioinformatics and Biology.

I loved the course so much! I have never programmed before and I've always been afraid of mathematics, but this course happened to be so exciting! I liked, how difficult (for me, at least) concepts are explained step-by step. I am sincerely grateful to the authors of the course.