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Learner Reviews & Feedback for Data Science Methodology by IBM

4.6
stars
17,621 ratings
2,165 reviews

About the Course

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!...

Top reviews

AG

May 13, 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

Jun 18, 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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76 - 100 of 2,172 Reviews for Data Science Methodology

By Guilherme P d C

May 6, 2019

For the case study presented, specially during modeling and evaluation phases, more elaboration would make the course better. Specially during modeling evaluations and ROC.

Also the course being conducted in a recorded slides is not appealing for student engagement. Would be great to have some videos with people explaining, like in the in course 1 of this program.

By Monserrat R

Jul 23, 2020

This is a very easy to understand course, I always have trouble staying focus while studying but this course is very fast and keeps you interested in the subject, it explains the methodology very well and its easy for you to retain all the information, and its very friendly for people without english as their first language, I highly recommend it, thanks a lot!

By Jason K

May 21, 2019

This course made me realize that people tend to jump to execution mode without even understanding what the business really want from them, and by not having a proper understanding they either produce a system that adds no value to the business, or they waste unnecessary time. The tools from this course is very helpful in any field that you are working in.

By Mark L

Jan 27, 2019

While the course is brief, exploring only one methodology in depth (predictive), it is well done. I could understand the exercises well. One fix would be a quiz asked what percentage was on a previous table. I did not take the time to memorize the values in the table as I don't see how that is relevant. A better quiz question could be been formulated.

By Alpesh G

Jun 20, 2021

It helps me in understanding the CRISP-DM, importance of Business & Data Understanding, iterative process from Feedback, Modeling, Refinement and Redeployment. The analogy with cooking task made it easier to grasp the concept. 'Top-down' and 'Bottom-up' approach to data science also explained very well. Thank you IBM and Coursera for this course.

By Deleted A

Aug 6, 2020

A very much intresting course along with the explaination of case study and hand on labs .

the best part is examples which is mentioned for deep understanding and clears the concepts from starting to a perfect coordination to each of the modules .

A special thanks to my Dear & Respected Alex aklson and Polong Lin Sir .

THANK U COURSERA + IBM .

By Varun V

Nov 11, 2018

This is a very nice course since understanding this course has helped us in thinking deep about various stages of a Data Science project. Moreover, the author has taken a case study and used that for explanation of all the concepts which made it look more like a story rather than just boring lectures. Very helpful and nicely organized.

By Tatyana F

Apr 22, 2020

It turned out that this theoretical block is quite complicated, since there are many details that must be taken into account when answering test questions. However, I am glad that I completed that course. Now I have a deep understanding of how to work with data at all stages. I thank the authors of the course for such quality content!

By Reza J

Dec 6, 2021

A great course before starting data science real projects. It is important to have a road map in every project where you create paths based on your goals and this course helps you out to do so. Also, the examples that this course use are simple but they are pretty close to real-world projects and helps understanding them a lot.

By Leonardo R

Jul 10, 2019

This course provides the perfect explanation of what goes into the data science methodology. The course guides students through an in depth analysis of each stage with examples and labs so they can follow along. The course also uses the data science method to solve a real world problem that one may encounter in their career.

By Ankit R

Apr 26, 2020

For a newbie,It is very important to understand how to solve a real world problem and for that its very important you should have knowledge of "How to approach?" and what all methods are required to achieve a statistical solution. This course helps me a lot in gaining those skills and looking ahead for other courses of IBM.

By Gideon R

Nov 3, 2018

Having a structured methodology is an essential part of one's work. Nothing is more tempting than shortcuts but we always end up regretting them. The Rollins approach to data science, when properly understood, really clarifies the sequence of steps involved in achieving a result that will satisfy the organizational needs.

By Dharmil D

Apr 2, 2022

A Wll Designed Course for beginners to Learn about data science methodology before applying Programming Skills however there is a suggetion from my side about Data Modelling stage as i am not a Statastics Student and don't know about what are the types of data Modelling so kindly Provide classifiction of Data Modelling.

By Ahmed H M

May 21, 2020

Great theoretical course for the whole process that Data Scientists go through. Explained well with case studies, however comes with a bit of intermediate python code to understand at this early stage, it forecasts what to expect next in the specialization from programming point of view, so get ready and enjoy the ride!

By Abelardo F

Jan 2, 2021

This course was very useful to fully understand the ideal Methodology for Data Science. From conceiving and formulating the correct questions to thinking analytically and chose which of the data models are the best for our problem. I really feel this is a basic course for anyone who wants to Excel in Data Science!

By Jason J D

Jul 30, 2019

Good course. Very important when it comes to implementing Data Science in real life. The instructor explains the life cycle and flow of the Data Science methodology along with an example scenario. Understanding and differentiating between the different phases of the methodology is much easier because of this.

By Barış P

Dec 13, 2019

Due to its approach to methodology, the course as a whole looks intimidating, but actually what it does is great way to teach a methodology, which is useful in both data science working space and academic environment. The course is quite easier than what it requires to fully understand the methodology.

By Jose J D

Sep 24, 2019

Absolutely Amazing Course. Clear, providing useful plug and play methodology. One of the best courses I have taken. One suggestion is to improve the quality of Slides on the presentation, I should have to evaluate with four stars due to this, but the quality is so high that I would go with five stars.

By Tsz K K L

May 23, 2021

Very useful course to tackle day to day workspace issues, especially if you're as a operations position. I was very inspired after taking this course and can relate to a lot of stuff that I'm working on at work. Definitely will apply this methodology and improve the process and achieve efficiency!

By Mohit S

Jun 15, 2020

This course will actually transits you the classroom, abstract teaching, or say for story telling to Real problems. In this course you will learn hoe to approach the problem and how one should think like a Data Scientist. Anyone who is interested to learn about Data Science must take this course.

By Pamudri B

Jan 13, 2021

This course gave me the exact idea of how to develop and integrate machine learning into my thesis in medicine. As a person who is completely new to the field, I have the knowledge now to develop a problem that would match my main research interest. Thank you for this amazing course. I loved it.

By James L M

Jul 2, 2020

The course is very comprehensive. I like the way explain each steps in a manner in which we could understand diagram on which the arrows are pointing. I hope they gave more examples or more practice so we could familiar each steps and the actions taken on their. All in all, the course is great!

By Sofia L

Dec 29, 2019

This course has completely blew my mind. I now see how data science can be applied to everything and can help find solutions to anything! from social issues to business. I thrilled that i have gained new insights from this course that I will put in practice from now on in every day in my life!

By Mauricio E M

Jun 9, 2020

What a course! totally surprised me. This course changed the way I approach any situation and problem not only in Data science but also in any day situation. You learn a methodology in order to aproach, work, analyze, structure, model and deploy your data science work. Thanks, very helpful!

By Rubén Q M

Apr 18, 2020

Comprendí que la metodología CRISP-DM es fundamental para la gestión de datos en Data Science, el éxito en el campo de la ciencia de datos depende de su capacidad para aplicar las herramientas correctas, en el momento correcto, en el orden correcto, para abordar el problema correcto.