HV
4.0Reviewed May 16, 2021
A bit more complex than what I would have hoped, but the material is still digestible. I think this course could be improve if the lecturer slow down a bit and spend more time on each topic
Data Science Methodology
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.
Status: Model Training
Status: Business Requirements
BeginnerCourse9 hours
Featured reviews
JG
5.0Reviewed Nov 29, 2019
This was a clear and concise overview of the methodology and using the case study really helped (although sometimes it got a bit advanced considering this comes before actually learning models).
PA
5.0Reviewed Apr 14, 2020
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.
MB
4.0Reviewed Sep 18, 2020
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.
HH
5.0Reviewed Sep 18, 2019
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.
TL
5.0Reviewed Mar 31, 2019
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.
AR
5.0Reviewed Nov 22, 2019
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.
GO
4.0Reviewed May 4, 2021
Great course for understanding data science and data related methodologies. Some parts that included machine learning algorithms confused me a little bit, but a little google search made it clear.
AP
4.0Reviewed Jan 20, 2020
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.
OZ
5.0Reviewed Jan 5, 2021
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 :)
CE
4.0Reviewed Aug 7, 2024
The course is well structured but the case studies were not well elaborated, felt like I was struggling to understand. Also, Data science methodology should be taught after a course in Python.
AK
4.0Reviewed Nov 17, 2023
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