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Introduction to Clinical Data Science

Introduction to Clinical Data Science

FREE

(51 customer reviews)
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9.0/10 (Our Score)
Product is rated as #37 in category Data Science

This course will prepare you to complete all parts of the Clinical Data Science Specialization. In this course you will learn how clinical data are generated, the format of these data, and the ethical and legal restrictions on these data. You will also learn enough SQL and R programming skills to be able to complete the entire Specialization – even if you are a beginner programmer. While you are taking this course you will have access to an actual clinical data set and a free, online computational environment for data science hosted by our Industry Partner Google Cloud. At the end of this course you will be prepared to embark on your clinical data science education journey, learning how to take data created by the healthcare system and improve the health of tomorrow’s patients. The University of Colorado is a recognized leader in higher education on the national and global stage. We collaborate to meet the diverse needs of our students and communities. We promote innovation, encourage discovery and support the extension of knowledge in ways unique to the state of Colorado and beyond.

Instructor Details

Dr. Wiley develops methods for using data from electronic health records for precision medicine discovery and implementation. She developed computational phenotyping algorithms for use in EHR-linked biobanks, investigated new algorithms for precision dosing of warfarin in African Americans, and has served as the lead informatician on an NIH Cancer Moonshot-funded project to create a comprehensive tobacco cessation service at the University of Colorado Cancer Center. She is a principle investigator in the Colorado Center for Personalized Medicine and an Assistant Professor in the Division of Biomedical Informatics and Personalized Medicine at the University of Colorado Anschutz Medical Campus. She has served as an ex officio member of the American Medical Informatics Association Board of Directors and is Vice-Chair of the AMIA 2019 Annual Symposium.

Specification: Introduction to Clinical Data Science

Duration

11 hours

Year

2019

Level

Intermediate

Certificate

Yes

Quizzes

Yes

51 reviews for Introduction to Clinical Data Science

4.7 out of 5
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  1. Fernando E L M

    Easy to understand, very professional and studying material is clear and relevant. I definitely recommend this course to jump into the clinical and healthcare data science world.

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  2. Ayush T

    This is a good introductory course on Clinical Data Science.

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  3. VIJAYA G

    I found Rstudio very confusing as there was no proper introduction or hands on example. Took a great deal in going through the links and addressing.

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  4. Travis H

    Good intro to the specialization. Learned a bit of R.

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  5. Anushadevi M

    Great introductory course for aspiring clinical data scientists

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  6. Seth R

    Great introduction to clinical data science covering a range of topics such as informatics, SQL, data science, R and the R Tidyverse.

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  7. Kristopher N

    Good introduction to see if you want to progress through the rest of the program

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  8. Robert W S

    Some material is inconsistent between the lectures and quizzes. Syntax of BigQuery does allow distinct queries, which was stated otherwise in the course material. Overall the content was good and was a nice introduction to the MIMICIII dataset.

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  9. Paolo D L

    The material is presented very clearly, and exercises are easy to understand and complete but really test one’s knowledge of the material.

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  10. Thomas J H

    Enjoyed that the instructor took a Tidyverse orientation, and matched it with the SQL query work. This connects two seemingly separate coding skills, and makes both easier to learn and master in a highly practical –– real–world functional –– way.

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  11. Joubert F

    Overall, good ! The introduction to R is confusing

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  12. Angela B

    I enjoyed this course. I felt the material presented was concise and easy to understand.

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  13. Rajesh J

    Great introduction to the clinical data science domain and toolsets

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  14. Jean–Michel B

    The class teaches a great combination of industry clinical data models concepts and sample data sets, access to cloud–based Bigquery from Google and RStudio, progressive coding exercises bringing it all together.

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  15. Rollie P

    Great introduction to fundamental concepts. May be challenging for those without any prior experience in SQL or R.

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  16. qianmengxiao

    very good course.Introduce me to EHR. Refresh on my SQL. And nice programming enviormnemt. Week 4 video could be more. R part is a bit weak.

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  17. Monique B W

    I really enjoyed this class. I had to go slowly because I was busy, but it was just the right amount of information for me.

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  18. Pothala R

    Nice course

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  19. Barbara J D

    I really enjoyed this course very much. I’m hoping completing the Clinical Data Science Specialty will give me enough experience with medical data so that I can get a job as a Medical Data Analyst or Data Warehouse/ETL developer for a medical company.

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  20. SHADRACK K

    I encourage people to take this course. its real time and it equips with real skill. the instructor is also so much great and into the point.

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  21. Adam R

    Good short introductory course. Clearly taught and scheduled.

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  22. Kazuki Y

    It was a nice starting point of R for me.

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  23. Mor K

    A nice introduction!

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  24. Mitchell G

    Great course! This course covers so much content in a condensed format without overwhelming the student. Great foundation for clinical data science. I’m looking forward to taking the subsequent courses!

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  25. Kamran k

    excellent module with hands–on exercises and quiz.

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  26. justin c

    Great intro and ability to build a base for early script writing.

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  27. Fidel G

    Great introduction to Clinical Data Science which provides you a bird view of how to prepare your mind and senses when you are tackle with the unknown of what to do and how to prepare your clinical data.

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  28. DEBRAH D A

    Before i started this course , i had no idea about SQL . this course introduced me to SQL, i did further research and learning on SQL, I was excited about it because of how interesting it is. Laura the Tutor is so amazing and its very easy to follow her. the only thing about this course content that i wish for was that if the SQL programming language part could be taught more. i had to use another platform to learn more about it. that is how i was able to finish most of assessment 3 and 4. but in all it is a great course and has opened up so many opportunities for me

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  29. Govindarajula A k

    When I started the course I was in impression that this would be like another run of the mill kind but after going through the modules, my perception got changed. I really picked up many terms and understood how data science techniques operate in Clinical domain. Certainly this course makes you to learn many new concepts, make you actually work on them. Planning to complete the remaining modules

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  30. Hahn S

    Very well organized! Explanations are good and detailed enough, most examples are helpful for understanding important concepts and acquiring essential skills and knowledge. I would strongly recommend this lecture to ones who are not in the medical/healthcare field, but need to work on clinical data. Thank you!

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  31. Vu T T T

    A good introduction to clinical data science course and useful for those who wants to tap into the field. However, prior knowledge of R is required as some concepts/functions are not fully explained in the course.

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  32. Yaser A

    Nice course I have learned new skills in data analysis

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  33. Arens J R M

    I really enjoyed everything in this class, I really loved it. It was an accumulation of new skills all along, almost everything was new to me: Google BigQuery, SQL, R language etc. Thank you for this opportunity!

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  34. wagne.ibrahima@gmail.com

    It was well structured/taught as online course

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  35. Hyun J K

    It’s a good course.

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  36. Enoch T

    One great course I will recommend to people. Had the chance to learn so much, especially about the MIMIC III dataset as I am using it for a project in AI. Thank you for this course.

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  37. Alexander S

    Very nice overview of a very complex topic. Somewhat superficial in some areas, but this is an introduction class and covered everything to an acceptable degree. A very intimidating topic.

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  38. Andres L

    The 2 first week were nice, the 3rd was good enough, the directions were not very clear and I had to spend certain time to find out what and how I had to do, the 4th week was awful, the directions were not friendly and I spent too much time trying to make RMarkdown work and doing the excercises. However I finally could complete it, I think the course meet the objective as an introduction course, the topic is complex but very interesting. Bigquery and RMarkdown access provided for this course was very useful and it was a very good experience.

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  39. Han–Yu H

    I didn’t know anything about coding and doubted myself of learning it. But this course provides very clear explanations and steps to code. I feel more confident now. For those, who have zero knowledge of computer science, this course is suitable to start.

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  40. Flora T M

    Very interesting course & I chose it among many offered by prestigious top university programs. After extensive research, I chose this course because of Coursera’s great reputation, and because the certification courses offered by U of Colorado specialize in the clinical data science niche, which I wanted to focus on. I plan to continue (next courses in this specialization). It’s not easy, but the course is very good & organized well. The attentive moderators answer questions quickly & don’t give up; they’re persistent & committed to resolving issues and ensuring the student understands the material.

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  41. William N

    Good introductory presentation

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  42. Kyle E B

    This course is a great intro to Clinical Data Science. I found some spelling/grammatical errors in the readings/quizzes. Also, I struggled a bit with some of the answers/writing the correct code; in these rare instances, I would look at the hint after and have no idea how I was supposed to know that. For example, I was having trouble mutating a column, and it turns out I was supposed to use the collect() function before mutation(). I don’t mind googling and figuring things out on my own; in fact, it is a critical skill for an analyst, but in an educational format, I wish they had brought up these functions in the reading.

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  43. Naveen B

    The most disappointing part was actually the one supposed to be the most important thing i.e. Week 4. More basic training should have been given about how and when to use R for data science application, What is the point of training course, when we ourselves have to figure out how to code with the help of one–page documentation (which did not have an organized structure)

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  44. Andrew J M

    Link the forum to the section we’re on so it decreases the barrier of entry to solving problems. This is not a problem with the course this is a problem with Coursera not developing an intuitive interface that allows users to quickly learn.

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  45. Kabakov B

    Good introductory course.

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  46. Zsolt

    Good intro to the field, but should spend more time and provide further reference to R.

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  47. DUONG H

    extremely interesting

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  48. Fatma A E

    Great course to get started into data science, clear cut explanations by Laura Wiley and assignments that make sense. Thank you!

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  49. John M

    I found the course very informative, which provides real clinical data and tools for acquiring the skills in clinical data science.

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  50. Michael B

    Very good course with quizzes that challenge a bit. Content is presented in a concise and didactically appropriate manner.

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  51. Mantu S

    I like the course.

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