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Avis et commentaires pour d'étudiants pour Data Science Methodology par IBM

4.6
stars
10,063 évaluations
982 avis

À propos du cours

Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn: - The major steps involved in tackling a data science problem. - The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment. - How data scientists think! LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

Meilleurs avis

AG

May 14, 2019

This is a proper course which will make you to understand each and every stage of Data science methodology. Lectures are well enough to make you think as a data scientist. Thank you fr this course :)

TX

Apr 01, 2019

It just totally rebuilds my mind in thinking about how I should approach solving problems. I feel that I'm learning strong framework for an evidence-based logical approach. Just like a consultant.

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826 - 850 sur 980 Avis pour Data Science Methodology

par Vincent Z

Jan 14, 2019

Very general and abstract presentation of what the Data Science recipe is. Still nothing practical three courses into the data science specialization... Had I followed the schedule, I would be 9 weeks in with nothing to show off. At least, this course gives a nice overview of what a data scientist will be doing, but I think this should have been presented in the first week of the first course, without necessarily testing it.

par Karel H

Mar 24, 2019

The exam for week 2 was terrible. The questions were way too tricky it was not necessary. Also I only was reviewed by one peer for my final assessment. This was bad because I deserved 100% and they gave me a only "Good" mark on one section probably because they figured out I gave them a "Good" mark on a section which they only did good on. More peer reviews should have been done than just one. I deserved a higher grade.

par Jennifer B

Dec 31, 2019

While it is important to demonstrate that there is more to data science than simply applying a tool, this course did little more than name some steps in the methodological process and give a one or two sentence description. The main case study was fine for me as I have a health background, but were full of undefined clinical terminology. The description of what belonged in each step is somewhat inconsistent.

par Saman R

Jul 22, 2019

The lecture videos are extremely verbose and monotonic. The features on the lecture slides have low resolution, and consequently, it's hard-to-impossible to read some of the contents on the charts and graphics. The lecturer talks non-stop without properly distinguishing between the steps. Lastly, the lecture slides are often redundant and have contents that don't really represent the step being lectured.

par Christian H

Jan 12, 2020

the course videos are sometimes not exactly to the point when describing what has to happen in the different stages of the provided methodology.

this makes doing the final peer-graded review somewhat difficult.

also the description of the final assessments objectives is super vague (especially compared to the very good descriptions of the final deliverables and assessments in the other courses!)

par Avinash B

Nov 18, 2019

Videos are at a high pace and the hospital use case introduces lots of information without proper slides,

when there is different text or points in the slides compared to the audio, it is hard to focus.

My sincere recommendation is to first talk the point in the slides, then explain the details. Also animations can be used to hide content and keep the focus on one item at a time.

par Reid N

May 13, 2019

A fairly odd way to teach the process of data science. I think this should be combined with the introduction to data science course and perhaps simplified/clarified. The amount of jargon between this course and the other courses is significantly greater, and while the course did a decent job, I still leave the course thinking, "hmm, what *exactly* did I learn from that class?"

par Hadi S A

Jun 27, 2019

Its an amazing course to give you an introduction to Data Science Methodology. But the case chosen was a hard case to understand specially if someone is a beginner in statistics and not into the medical field. I wasn't the only one who got confused while using the methodology on the case shown. Hopefully, a simpler case gets introduced in future.

par Dita A

Mar 04, 2019

The course is good but the way the example is explained is a bit confusing, especially the when jumping from study content/material to the example.

The peer to peer review for the final assignment is veeeerrryyy subjective. I had to submit 3 times (with little to no change on my answer) in order to pass. Good luck on getting a nice reviewer! :)

par Abraham Z

Jan 03, 2020

IBM Developer Skills Network was have connection issues during the lessons. I worked on this course at several different locations on two different PC environments. One PC was a corporate controlled windows system, and the other was personal windows system. These connection issues distracted from the course content.

par Rakshit K

Sep 11, 2018

If you could have explained the terms related to machine learning more and if you could have spend more time on understanding the Actual problem of the case study and then slowly built up the solution it would have been great course. I loved the organization of course but not the flow of the course. Thank You.

par Muhammad U T

May 31, 2019

It provides a satisfactory overview of the data Science methodology, but the slides and the videos does not suffice the needs to fully understand the concepts and the Labs. Supplementary readings for this course are MANDATORY to understand and fill the knowledge gaps for several topics named in the videos.

par Esteban P

Jul 19, 2019

I think that they should define more the specific concepts of all the states of the methodology, and then make references to "hypothetical" cases. Personally, I lost more trying to understand the examples and I had to go to find more specific information in other sources.

par Mak C Y

Apr 26, 2019

Grateful if more explanation or more cases can be given. Also, I found that the final assignment has a mistake, making the total available scores changed from 10 to 9, which force us to make a "perfect answer" to get almost a full mark (the passing mark is 8 marks).

par Suyog J

Oct 09, 2019

Appreciate the content so far. This can be though made more in-depth when it comes to hands on. Including graded level hands on practice can enhance the learning experience the students get from this course.

Thanks for enabling us with all through the course.

par Chaojie W

Oct 26, 2019

I understand that this video want to give a full image of Data Science. But its case study including too much low-frequency vocabulary / terminology, which is an obstacle to beginner. And some reading material 's exercise is not very necessary...

par Alina T

Jun 27, 2019

I found this course to be a little bit too vague and theoretical, and hence, difficult to understand sometimes. I personally prefer to study and work with hands-on and applied aspects of Data Science instead of theory and vague definitions.

par Daniel T F

May 16, 2019

Presents you a good overview according the main topics of data science methodology. The case study is a good example to illustrate to content. But with respect to my experience the labs are very limited concerning the learning effect.

par Ivo M

Dec 13, 2018

The narrator was quite fast and I could not engage with the video lectures so well on this course. Consider review the Hospital case study too, which is quite complex when trying to understand the new concepts on the methodology.

par MUNIB U R

Jun 22, 2019

The course is a bit confusing for a beginner, the concepts should be clearly explained, the prediction model and the descriptive model should be taken in different videos.The learner should understand the difference clearly.

par Roy R

Apr 04, 2019

Difficult being able to apply the final test to the complete module objectives. Though it was good foundation, felt it should be split into several workable modules/stages instead of all 10 methodology steps at once.

par Yves J

Aug 15, 2019

Methodology course should be done at the end of the whole certificate course or at least when the student has a better understanding of all the statistical methods available (regression, machine learning..)

par Roshan P

Apr 17, 2019

This could be little bit more in detail. The content and the methodology was introduced but could be more in detail about all the analytical approaches available and why we chose decision trees for the CHF.

par Jason L

Jun 25, 2019

Good intro, but I felt the introduction to python might have been better before this subject. Could have spent more time on the Labs, seemed more complicated if you didn't have any background in coding.

par Kate O

May 09, 2019

This course provides a clear approach to data science methodology. The lab exercises are difficult to open and use, but the case study presented in the instructional videos is informative.