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

4.6
étoiles
14,439 évaluations
1,658 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 :)

JM

Feb 27, 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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176 - 200 sur 1,645 Avis pour Data Science Methodology

par Aditya C

Nov 03, 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 Alessandro S E

Jan 02, 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 Muzahidur R

May 30, 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

Jan 07, 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

Apr 18, 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 Clarence E Y

Jan 04, 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

Sep 13, 2019

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

par Lawrence B

Jan 25, 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 T L

Oct 15, 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

Sep 13, 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

May 02, 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

Sep 08, 2019

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

Highly recommended for beginners.

par Bhavani S R M

Jan 30, 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.

par Rohit K

May 09, 2020

If you really want to become a data scientist then you are at the right place.This course literally teaches you how to think like a data scientist.

par Caroline V j a

Jul 10, 2020

This covers all the topics we need to know , regardless of beginner or experienced person. The topics are clearly described in understandable way.

par Christine C

Aug 04, 2019

This the best course I have taken in coursera so far. The concepts are explained in detail and the case studies are simple, yet very informative.

par Sarah A S H

May 04, 2020

I truly enjoy this course. The way it is conducted has helped me to understand easily, grasping the concepts, and the objectives of this course.

par Pedro C G

Dec 23, 2019

Great course to know the methodology proposed to be used by IBM.

I think the methodology itself is a very good one to achieve answers using data.

par Abdullah E C

Sep 28, 2019

I think this course was the most important part of the course series. Because shows you the steps that should be followed by the data scientist.

par Manivannan D

Jan 16, 2019

This course is very much interesting and course metrical is good. Also motivating the students by providing practical Lab facility and exercises

par Tholkappiyan A

Jun 14, 2020

I like this course very much as it was designed to evaluate our understand at each stage and also the lab is a great way to learn in practical.

par Sarthak A

Jul 25, 2020

Good Introduction to how to approach a problem for people who are new to the world of data. Kudos to the creators to keep the language simple.

par Ben M

Jul 18, 2020

Great overview of a practical method that can defintiely be used. Plus some great code to show the steps you would take in the modelling steps

par Sutapan P

Jan 02, 2020

very informative course. provide details on each step of Data Science methodology.

enjoyed the final assignment because of all relevant topics.

par Cebe C

Mar 13, 2020

It's an amazing course that make you half a data scientist. The rest half is learning the tools to follow the steps given in the methodology.