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

4.6
étoiles
16,772 évaluations
2,038 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!...

Meilleurs avis

TM
18 juin 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!

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 :)

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226 - 250 sur 2,040 Avis pour Data Science Methodology

par Krishno S

19 juin 2020

Excellent Course! Very nicely designed and delivered. The Data Science course is easy to grasp and made very interesting delivery. I am excited to learn more.

par Jennifer K

1 avr. 2020

It is helpful for me to learn the process how to do with data science methodology.

Thank you for your great teaching and quiz to help me improve my new skills.

par Steve M

23 sept. 2020

Excellent course with tons of great information. It provides a great step-by-step review of the methodology while still keeping things somewhat challenging.

par Ajay S P

1 févr. 2020

Change my perspective towards the data science.

Before starting to step in towards data science every individual should understand its methodology completely.

par Harish K N

7 juil. 2019

Awesome course! Thanks for putting together this wonderful course. Well prepared labs, and some informative discussions in the forum are the additional pros.

par Aditya C

2 nov. 2018

Didactic course, supported with the assignment to conclude, gives you an understanding of the data science methodology, meticulously. I'll give it a 5-star!!

par Alfred D H

26 août 2021

A good primer in the steps a Data Scientist needs to follow to answer the questions developed by the Business using data made available for post processing.

par Aditya S

20 sept. 2021

By studying this course I can find out step by step processing carried out by a data scientist from the beginning of the project to the end of the project.

par Dalana O

3 mai 2021

I learned a lot about the data science methodology, I really liked the final assignment, it was helpful to put together the Methodology in a business plan.

par Alessandro S E

1 janv. 2020

It was a challenge for me to get on with the tasks and especially to understand all the concepts. But I believe it will be of great value to my profession.

par Jose M

19 oct. 2020

This course with you a good base to build your career as a data scientist. A follow a methodology is a must in order to success in every job. Nice course!

par Muzahidur R

30 mai 2020

It was a short course focused mainly on the steps of a data science procedure. All the 9 courses of IBM Data Science Professional Certificate is valuable.

par Dinara K

7 janv. 2020

Very interesting course with lots of case study examples, with great lab works. Course gives opportunity to understand the methodology of the Data Science

par Sadiq S H G

17 avr. 2019

A very wonderful course filled with interesting information. I would like to thank IBM as well as the Coursera platform as well as the course Instructors.

par A J

7 déc. 2020

The IBM Data Science courses are perfect for those who are starting out in the data science field or looking to build their skill set.. Highly recommend

par Clarence E Y

3 janv. 2019

This course is rigorous but well paced and valuable to get a modicum of understanding about how data scientists work and collaborate with business teams.

par Lakshminarayana D

13 sept. 2019

Great Learning in understanding the step by step process from business understanding, analytics approach to modelling, evaluation, deployment, feedback.

par Myles M

18 sept. 2020

Great course, very well thought out. This course is very clear about the learning objectives and makes sure you really lock in the learning objectives.

par Lawrence B

25 janv. 2019

I am enjoying the course very much. I would like to see a reference book to download or content to easily look at to follow certain code, and apply it.

par Toan L T

15 oct. 2018

Great job at introducing the Data Science Methodology.

The case-study and interactive labs really help illustrate what the lessons is about in practice.

par Vincent L

13 sept. 2018

Great as an intro to data science, giving us a structured approach from the start.

I would detail the steps more formally in the Working with Data part.

par Sesha C M V

2 mai 2020

Course is very helpful to understands the how to go with analytic approach through methodology.

It good start for the any data science and AI aspirant

par Shikha T

8 sept. 2019

Course describes various steps followed for Data science projects with quite practical reasoning, and understanding.

Highly recommended for beginners.

par Marwan K

23 juil. 2021

I​ am really glad to pass this course in IBM Data Science Professional Certificate.

T​hank you Coursera.

T​hank you IBM.

T​hank you to all instructors.

par Rohit M

30 janv. 2019

This is probably the most important part of being a data scientist. The course uses a case study to demonstrate the methodology and how to apply it.