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 :)
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.
By Cebe C•
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.
By Akash V•
This course gives a detailed outline of data science methodology and approach of a data scientist.
Thank you so much for offering this course.
By Nurullah K•
The course was effective,it was a little bit hard but it was instructive,i am happy that i finished a step more in the data science journey.
By Diana T•
Very useful and interesting, I like the Labs and the Case studies, they help you to understand how the methodology is performed step by step.
By Ziaur R•
I found this invaluable for understanding the process of a Data Science Project from start to finish with the help of the Case Study example
By Yatan U•
A lot of content. Enough information. The notes in the videos could be more to the point and corresponding to what the instructor is saying.
By SWARNAVA B•
Really enjoyed and learning the various data science methodology, which helped me a lot to implement an write my project on Hospitalization'
By Christian J•
I imagine this to be the foundation of any data science problem, and will probably be knowledge used for the rest of my data science career.
By Matheus L T A•
Great course, with a lot of content! This methodology can actually be applied on most problems you will find in life and help to solve them!
By Lebogang K M•
This course was really easy to understand and it summed up the process quite neatly. Could use an extra assignment though. Take the course!
By Pranay C•
This course is where you wet your feet for Data Science. This course teaches you the essential steps required for performing Data Analysis.
By Alex C•
This course gives the user a framework to be able to tackle Data Science problems. Very interesting material, backed up with a case study.
By Shubham K•
Amazingly explained with the help of labs and case studies! Hoping that the subsequent courses will be taught using the similar approach!
By Luis M•
Very thorough introduction to IBM's data science methodology. The best training I've received on the subject of the data science process.
By Romeo C•
This course was a great introduction to the iterative process used by data scientists to go from problem to solution. I highly enjoyed it!
By Pedro F•
More dense, long and difficult than other introductory courses, but needed to secure the understanding of the DS Methodology. Recommended!
By Avoaja U c•
Great course, gentle introduction to data science methodologies. And all the tools necessary to complete the course are provided for free.
By Brahim A•
Great course! I learned much on data science methodology. Notes, texts, videos and audios were perfect. Thanks for that!
By Ogbonnaya O•
Excellent. This clearly answers my questions on my thesis. I have been looking which methodology is suitable for data science projects
By Nikhil J•
Perfectly explained the Data Science methodology. The stages in developing a solution to a Data-centric problem. Definitely recommended!
By Kenneth W•
Spending the time needed to fully understand the course material will greatly enhance your experience as a new beginning data scientist.
By Hashum A•
i this course is excellent for better understanding how we understand the problem and what steps by doing this we can achieve the goals
By Demetrius M•
This course is amazing for understanding how to execute a Data Science project! I learned a lot and can't wait to apply the knowledge!
By Augustin C•
Some notions could be explained a bit more in detailled - or the author should suggest the trainee to refer to applicable litterature
By Fang S•
Data Science is an interdisciplinary field of management, business, project management, statistics, analytics, and computer science.