This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed. This is the first course in the Genomic Data Science Specialization.
CS
Fantastic course from two true authorities in the field. Great examples, and I was surprisingly enthralled by the statistical section; turns out I just never had the right teacher!
LK
This course had gave me the overview of the statistical analyses for genomic data analysis. This is useful for me as I can employ those statistical Analyses knowledge in the near future
JG
The course is very informative and straightforward. It allows learners to grasp the basics effectively and highlights the foundational concept needed for the next competencies.
EO
Clear and concise. Ministered by researchers with outstanding background in research, able to translate topics of relatively high complexity into easy language for a broad audience.
MR
Very good introductory course. It's a lot of material to cover for a newbie, but if you have some background, you will find you progress pretty quickly. Enjoyable, engaging, fun and useful.
SM
This course is very well suitable for beginners. I am eagerly waiting to start the next course of the specialization for deeper understanding. Although, this course was very informative.
HL
Nice module!!! I've learnt a lot!! I love the instructors so much, they not only taught us the knowledge clearly but explained them in plain English. Thanks!
SZ
The tutorial videos were concise while delivering the essential material. The speakers were also engaging and it was a joy to watch them. Overall fairly satisfied with the course.
AN
Thanks to everyone who made this. Such can wait to start the second course. h a superb course; it started slowly and sort of an easy thing, but the last lecture was phenomenal
BS
The final project was way more work than any of the other weeks (10 hours!), but it was definitely worth stumbling my way around Galaxy and foreign genomic terms for that long.
KK
Relatively nice introduction course, contents are maybe rather limited, yet as an instructive course, it does provide a clear overview which correlates well with the required answers for the quizzes!
AA
It is a great introduction course if you really don't know anything about the field. But if you think you have got the basics down, that means this course will be too easy for you.
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Great introduction to Genomics. The instructors really laid out the practical terms and gave great resources. Weeks 3 and 4 ramp up in difficulty, so some outside research in statistics is helpful.
This course provides a gentle introduction to the concepts and terminology associated with genomics. As someone who never took a biology course in high school or university, this course is perfect.
Relatively nice introduction course, contents are maybe rather limited, yet as an instructive course, it does provide a clear overview which correlates well with the required answers for the quizzes!
It is a great introduction course if you really don't know anything about the field. But if you think you have got the basics down, that means this course will be too easy for you.
This is my first course in Genomic Technologies (and one I completed overall). I was taking this course bit lightly for being the introductory/basic course but I have learnt a number of new things: Introduction to some stats terms I overlooked/haven't learnt before like p-test and confounders, the incredible example of data-counterfeiting in the academia and how PCR and next-gen sequencing technologies work. Although I couldn't learn in depth, which is obvious since its first of the 8 course specialization, so I am anxious to take the next course - this specialization is looking very exciting.
Have tried a few other courses around introduction to genomic technologies but this is the best structured course I have taken. Loved the course project as it gives a good insight on how to read scientific papers and what is expected from a genomic scientist. The only point would be to improve the statistics content(week 4) and make it more beginner friendly especially when it comes to p-values.
A good basic introduction. Might have been nice to have had recommendations for further reading for those who were interested.
I have done the data sciences specialization from JHU and that was 4 star on 5. Compared to that, this specialization is pretty bad.
Not worth doing this specialization. Instructors are clueless on the plan
I found the course to be very clear and informative. I believe the molecular biology aspect was easy enough for someone without a background in biology or biochemistry to understand. Also, the computer science and statistical aspects were also explained in a clear way.
Very good introductory course. It's a lot of material to cover for a newbie, but if you have some background, you will find you progress pretty quickly. Enjoyable, engaging, fun and useful.
It seemed a little too easy, especially for the timeline given. Seemed like there should have been more information, or have gone more in-depth
Good intro for people who don't have any background, a little too simple for people who already work in this criteria or have knowledge about
Great way of delivering information.
The initial lectures on introduction to genomics are very engaging and good starting point for everyone who slightly touched that topic before and is interested in both history and recent developments in the area.
The week focusing on software engineering doesn't seem to be a good fit for such training. Most of the content is dedicated to extremely trivial computer science topics hardly related with bioinformatics. Only last several minutes give examples of bioIT software and systems.
The week with statistics is good only if you posses solid knowledge on statistics. Then it serves as a good recap. Otherwise you might be completely lost 5 min into the content, e.g. there are much better explanations of p-value and family-wise error out there in internet than the one provided in the course.
The idea of a project to go through a research paper and answer the questions about it was fantastic! Very good way to cement what you learned.
Overall: 3 stars. I would give 4 if not for trivial and rather useless computer science intro. At few points, the pace should be adjusted (e.g. statistics).
While I wasn't expecting heavy material for an intro course, this course did not reach even a 101 level in my opinion. Take this course if you have never heard of biology or computer science or statistics but avoid if you know even a little about these subjects. Sometimes the quiz questions asked about details not covered in videos/papers, which was pointless and frustrating.
Good class but incredibly basic. Needs to go a bit more in depth. Feels rushed.
Quite good explanation of molecular biology and statistics. Hope the narrator can lower down the speed, since it is a little tough for a non-native English speaker to catch-up with it (Though the pronunciation is very clear)
Fantastic course from two true authorities in the field. Great examples, and I was surprisingly enthralled by the statistical section; turns out I just never had the right teacher!
Very good introduction.
Gained good knowledge