- 9 reviews
- 9 completed
This is a very useful course in Machine Learning that teaches us how to use the R based packages such as CARET for applying machine learning techniques. The course project helps understand how these techniques are applied in real world applications and develop useful insights.
This is a very useful course in the Data Science Specialization that teaches us how to present the results of our data analysis using Shiny, Slidify and other R based data presentation tools. It also introduces open source charting APIs that we could use in our data analysis applications.
This is a very useful course in Data Analysis wherein we learn to explore the data sets and explore relationships between the variables for further analysis. It acts as a foundation for developing further models based on regression analysis or machine learning.
This course on Regression Models helps develop statistical models for analyzing data sets. These regression models help explore the relationships between the variables and build the first analytic models before any machine learning techniques are applied. The models covered are very useful for scientific research.
This is a very useful course in Data Science where in we learn to use R tools for getting data from various sources, cleaning the data and staging it for further analysis. The techniques are important to learn for subsequent courses in this specialization.
This is the first course in the Data Science Specialization series by Johns Hopkins University taught on Coursera. It introduces all the tools necessary for subsequent courses on data science and gives a driving motivation for the specialization.
This was a very useful course in Statistical Inference where in all the fundamentals are taught in a very clear manner, setting the stage for the subsequent course on regression models. The course is taught with examples on use of Statistical Inference in biostatistics and these examples are very helpful in understanding the concepts.
I found the exploratory techniques described in this course to be useful. The course content was well explained and I found the notes to be useful in completing the assignments.
I found the learning curve on this course to be very steep. I had to struggle a bit on the project but the discussion forums and a little online search was able to help me get to the right answers. I find the skills learned to be very useful in the subsequent courses on exploratory data analysis, statistical inference and regression models. If you are confident using plyr and dplyr libraries, it gives you more time to focus on the important parts of the code during analysis.