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Opiniones y comentarios de aprendices correspondientes a Data Science Methodology por parte de Habilidades en redes de IBM

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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!...

Principales reseñas

AG

13 de may. de 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 :)

TM

18 de jun. de 2021

Very interesting course. It shed a light on what the structured approach really is. It's worth to pause for a moment with every step of the methodology and think how to apply it in real life. Thanks!

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126 - 150 de 2,222 revisiones para Data Science Methodology

por Alexandra H

2 de ene. de 2021

While being familiar with the process of research methodology I did very much enjoy learning the data science terminology associated with it. The only issue I ran into with the particular module was that the instructions for the labs were out of data.

por Jeff L

23 de ene. de 2020

It's really a lot of information than I expected, but it is certainly helpful for helping me to further understand data science. My only suggestion is to include more explanation to the code in the labs to make it easier to interpret for the students.

por Bibhu A P

5 de nov. de 2019

The methodology was really great. Though this is somewhat a modified version of the CRSIP-DM methodology being used in Data mining. The labs were wonderfully set up to understand the topic. The case study was the most interesting aspect of the course.

por Raphael N

4 de mar. de 2019

This was one of the trickiest courses I have taken yet. I have had to re-read the documents and watch the presentations to get the concept clearly. I highly recommend it to anyone willing to be patient to understand the under-workings of data science.

por Ivan F

4 de abr. de 2022

I was a bit reluctant to do this course, however, after starting I could not stop. I think this course presents the DS methodology in the easiest way to understand for beginners. The examples that the instructor shows are clear and easy to relate to.

por Juan M H T

11 de dic. de 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.

por Marat M

30 de oct. de 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!

por Louis C C I

29 de dic. de 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.

por Amitayu B

16 de dic. de 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.

por Thomas P

2 de abr. de 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.

por Ankit T

26 de abr. de 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.

por Anh D

6 de sep. de 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

por Sabra H

23 de may. de 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.

por Miguel V

6 de ago. de 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

por Aastha M

20 de ago. de 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!

por Amy P

26 de abr. de 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.

por Isis S C

20 de ene. de 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.

por Jafed E G

6 de jul. de 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

por Asresh K

13 de feb. de 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.

por Ferenc F P

26 de feb. de 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.

por hassan s

14 de ago. de 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.

por Sérgio L

27 de may. de 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.

por Lucas F M

15 de ene. de 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.

por Kwadwo A

21 de nov. de 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.

por Fred R

18 de dic. de 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.