This course gives you a very good idea about:
- The different parts of the whole data science pipeline.
- And how to work through the whole data science pipeline using R.
If you had no programming experience, this course will be really hard! If you are new to the field of data science or analytics, this may not be the first resource you should go for. A decent understanding of statistics, ML techniques would be helpful in deriving the most out of this courses.
Specification: Johns Hopkins Data Science Specialization
|Free Trial (in days)|
|Duration (in months)|
|What will you learn?|
|Programming Language Used|
1. An introduction to the main tools and ideas in the data scientist's toolbox.
|Graded quizzes & assignments|
2 reviews for Johns Hopkins Data Science Specialization
- Course give a good foundation to Data Science.
- Most of the DS topics are covered, making it one of the most “complete” in terms of delivering a DS pipeline.
- They tried to cover topics as much as they can but didn't cover deeply.
- Statistical Inference and Regression Models didn't provide basic foundations (lectures seem rushed). Some participants had to go multiple websites to learn basic concepts.
- Practical Machine Learning will not teach you the Machine Learning algorithms from scratch but just teaches you to how to use different R packages to perform Modelling and Machine Learning tasks on your data.
- The Capstone experience was mostly DIY with very little guidance from lectures and notes. You're pretty much on your own.
- Some lecture material was sub-par (statistical inference) compared to Khan Academy.