If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. In this course, you will learn and then apply this methodology that you can use to tackle any Data Science scenario. You’ll explore two notable data science methodologies, Foundational Data Science Methodology, and the six-stage CRISP-DM data science methodology, and learn how to apply these data science methodologies. Most established data scientists follow these or similar methodologies for solving data science problems. Begin by learning about forming the business/research problem Learn how data scientists obtain, prepare, and analyze data. Discover how applying data science methodology practices helps ensure that the data used for problem-solving is relevant and properly manipulated to address the question. Next, learn about building the data model, deploying that model, data storytelling, and obtaining feedback You’ll think like a data scientist and develop your data science methodology skills using a real-world inspired scenario through progressive labs hosted within Jupyter Notebooks and using Python.
This was a critical course for me. Understanding the data scientists workflow which includes customer\client interaction has help me in understanding how to proceed in future endeavors.
It is self paced giving a good grounding on the subject provided you are an inquisitive & enthusiastic learner. It does not provide a deep dive but gives a road map for self learning.
It is a good course, teaching about the general process and life cycle of a data science project. Excellent tips are provided. Overall, I feel it was lacking a bit in content for 3 weeks.
It was a good course with very easy to understand material and methodology.In my opinion additional optional reading resources or case study links is required for this to be a 5 star course.
It just totally rebuilds my mind in thinking about how I should approach solving problems. I feel that I'm learning strong framework for an evidence-based logical approach. Just like a consultant.
It is a very important course to understand the procedures and thought processes behind data science. I strongly recommend it to those who are unfamiliar with data science or reserach methodology.
A very important course to develop a fundamental understanding of data science. Excellent in-course example to simplify the process of learning (think of it as a recipe in cooking). Enjoyed it.
Very enriching course. I really liked the content of this course as it has guided me the basic framework of solving any data science problem. the assignment is also fun and enjoyable to do.
It's a very good course for getting the basic idea of the methodology of data science. It will help to get grip on how to proceed to a problem in a systematic manner for getting good results.
in this course step by step guide for beginner data scientists is illustrated with practical application and real examples with codes! best course in this specialization so far. Enjoy it :)
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 :)
Great course by IBM. Would like instructors to have better communication skills. As the instructor in week 2 and 3 did not have that strong communication skills as compared to week 1 . Overall 8/10
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This one is fairly painful to sit through and needlessly complex. Other sites have explained this much simpler and clearer than here
Nothing is discussed in details. For people know nothing about data science, many topics are not explained and they won't understand anything valuable; for people already have a background in data science, the topics are useless and too shallow.
1) This descriptions in this course are very dull. They need to be supported by better examples which do not include a lot of terminology specific to the topic.
2) The questions in the videos can be better designed to evaluate the students' knowledge about the topic, e.g., letting them apply their knowledge in new examples. Some questions are redundant such as the name of the person who designed the data science methodology or questions specific to the case study and does not necessarily provide insight into general concepts.
3) Simply reading what is in the slides is not a good use of videos and cannot keep the focus of the students for a long time.
4) This course might be located after the Python for Data Science course or even later so that the students could have a more meaningful final assignment, actually applying what they learned on a small data set.
5) Knowing a subject and teaching a subject are two different things. I hope you consult a university professor in the field about how to teach these courses. There is a lot of room for improvement in terms of the pedagogical perspective.
Quizzes quiz on material not covered in the course or directed to externally. Most of the quizzes are word games and do not apply concepts covered in the material. Everything from how disconnected the quiz questions are compared to available information provided in the course to the peer-graded final assignment show little or now effort was put into composing this course.
Instead of CHF the case study should be change to something which everyone can understand.
The example should change to a easier one. This example is hard to understand.
Course was dry, and not very engaging. I did not get much out of it, and it seems like most people only spend a couple of hours taking this course. The labs were more interesting, I had more fun looking at the code that was not explained or part of the course, than learning the actual course material.
Too complex of a case study to understand stuff. Also, too boring and theoretical and very less interactive.
Really difficult content to digest without much written information. This course needs to provide more readings and the videos need to provide more text, as opposed to relying on voice instruction.
It just totally rebuilds my mind in thinking about how I should approach solving problems. I feel that I'm learning strong framework for an evidence-based logical approach. Just like a consultant.
This Course is pretty good and concepts are so nice but the example taken to describe the Data Science Methodology is not so good. Could have been taken a better example with far better presentation skills.
This course is not as engaging or organized as well as the first two courses in the Data Science Certificate. I found it to be unnecessarily complicated and confusing due to jumping around a bit in terms of steps in the process.
The case study given was very confusing. Even, the tutor did not do a great job explaining and facilitating the case study. I only understand it better through the cooking metaphor. They should have choose a better and simpler case study.
This was a good course. It was an overview of the entire data science process, which was helpful for me since I didn't really have a good understanding of what data science meant before this class. Now I have a much better understanding of what people mean when they say data science. Also, this class gives a good orientation for other courses; for example, I would see "data mining" courses on Coursera and not understand how that fit in with data science. Now I do. I would recommend this course for people very new at programming and data science, like me.
Except for the lab parts, it is a very poor course which covered a very important topic that should build the initial stone in working as data scientist but the instructors ruined my experience. They were monotonous, did not to explain in simpler ways. they explained from they high end expert and the slides were poor and not interactive and verry boring and it was extremely difficult to keep focus with them.
terrible course
More or less a complete waste of time. Some of the Jupyter notebooks were interesting, but not enough to make this anything other than a way to stretch out your enrollment period in the course...
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.
I actually enjoyed this class... I didnt expect to based on the reviews going in, but it was interesting and I did learn a lot. That being said however, the material was a little dry and the case study was a little more complicated than it should be for someone taking an intro class to data science methodology. They may be perfect for someone in the industry, but I spent a lot of time on google looking up what the case study was talking about - I learned a lot more in the labs with food and ingredients and recipes
Was a bit hard to understand for a complete beginner without a statistical background. Hospital example was a bit difficult to follow as well.