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

4.6
étoiles
15,441 évaluations
1,830 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
13 mai 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 :)

JM
26 févr. 2020

Very informative step-by-step guide of how to create a data science project. Course presents concepts in an engaging way and the quizzes and assignments helped in understanding the overall material.

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101 - 125 sur 1,814 Avis pour Data Science Methodology

par Juan M H T

11 déc. 2020

This is not a general overview, it's a complete scann to Data Science Methodology that allowed me to see the complete development of a Data Science project with the usage of the tools and intervention of roles previously reviewed in the past courses.

par Marat M

30 oct. 2020

Very interesting and useful course. Final project is also very useful, since it allows to apply immediately the learning skills creating a new brief data science project. I am very impressed by this course and I would like to thank the instructors!

par Louis C

29 déc. 2020

Its a great introduction to the data science methodology. The only thing I wish is that they go a little bit slower in the videos. They're talking about something and I'm reading the slides and then it just shifts over to a new slide fairly quick.

par Amitayu B

16 déc. 2020

Interesting course, only video-sound was a bit low. Learned the basic steps Business understanding, Analytic approach, Data requirement, Data collection, Data understanding, Data preparation, Modelling, Model evaluation, Deployment, and Feedback.

par Thomas P

2 avr. 2019

Good introduction to the methods used by data science. It was a clear walk through the different stages of the process. A good outline to keep available when tackling basic data science problems. I will print out the method and use it at work.

par Ankit T

26 avr. 2020

It is a great course in understanding the concepts of how data scientist starts with a business problem and transform that into a solution using data. It takes you through the journey from the problem until the solution and how you go about it.

par Anh D

6 sept. 2020

The course is really good which makes me have a new vision about Data Science, especially the part of Ungraded External Tools. Although there are a few bit of confusing concepts, I have learned so much from the course. Thank you, instructors

par Sabra H

23 mai 2020

its good to know about methodology before going deep to a better ideal, i think this course should be after next courses, because practical labs was hard, if there was practical lab that we can do it all by myself, it will be more awesome.

par Miguel V

6 août 2020

This course was actually extremely useful in understanding the mindset of a data scientist. As someone in academia, there has always been an inherent disjunction between scholastic and business methodology. This course bridges that gap. :D

par Aastha M

20 août 2020

This is a very informative course on how the data science methodology process is carried forward when a real problem is encountered. Each phase has been taught with good relatable examples which simplifies the learning process. Thank you!

par Amy P

26 avr. 2019

Very thorough, thanks to excellent narration that had just the right enough repetition. Helpful use of diagrams to reiterate concepts. The Jupyter notebook labs were a fantastic way to illustrate the stages of data science methodology.

par Isis S C

20 janv. 2020

Fantástico! Curso super eficiente, traz rápida assimilação da abordagem de Data Science, introduzindo, simultaneamente, Jupyter Notebooks: exmplo e na prática. Os exercícios peer reviewed criam uma deliciosa oportunidade de interação.

par Jafed E G

6 juil. 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

par Asresh K

13 févr. 2020

An amazing course which teaches you the path to choose in order to solve data related business problems. The approaches mentioned in this course are very logical and awesome and can be used to solve most of the data science problems.

par Ferenc F P

26 févr. 2019

This course is excellent, as it helps you understand the way of working, how you should carry out a data science project, and how your final report should look like. This course will help you in making a good report for the Capstone.

par hassan s

14 août 2019

That was great fun learning a lot of stuff regarding the Data Science Modeling. This is a perfect course to understand and come to a problem solving model for any data scientist. Really changed my perception of solving the problem.

par Sérgio L

27 mai 2019

This course gave me a very important and useful framework, as I've been working with data analysis for more than ten years without any methodology to rely on. It is definetely necessary for whoever wants to deal with data analysis.

par Lucas F M

15 janv. 2021

Very nice review of the steps needed to develop a project in Data Science. It may not be too much of a surprise for people who have a background in Science, but it still well put together and interesting. Nice case study included.

par Kwadwo A

21 nov. 2020

My first time ever using Coursera. I feel justice was done to the topic. It was very detailed ad enjoyed each day i reviewed the resources on this topic. Thank you for such a platform. Looking forward to completing future courses.

par Fred R

18 déc. 2019

A very clear and instructive introduction to the Data Science process, from business question to results, with a very pedagogic explanation of all the stages in the process and the specific problems that characterize each of them.

par Zabihullah

31 déc. 2019

Satisfying with the materials provided but the issue is the example used in lectures. It is better to find some common examples to be understandable for all fields of studies rather than talking about patients and medical things.

par Louis J

23 sept. 2019

Very good! Would be interesting to go deeper and apply the whole data science methodology to a real case, write the code and detail deeply each step. I am searching exercises online to practice similar to real business scenarios.

par William B L

13 mars 2019

The methodology presented is robustly presented, with detailed descriptions of each step, the relation to those steps around it, the progress made at each step, and what is handed off between steps. I would strongly recommend it

par Abilio R D

18 nov. 2019

Excellent course. The data science methodology learned in this course can be used to solve any problem present by one stakeholder. This course topic is the foundation for any one that would like to become a good data scientist.

par Francisco B L

1 févr. 2019

This is the best Course in the Data Science Specialization so far. Not only does it structure the approach to tackle probles in Data Science but the Labs also gie you a very good idea on how powerful the tools are. Great!