I am a graduate student in Civil Engineering. For the analyses of road traffic data (vehicle trajectories as time series) I work with big data sets mostly about a million data points or more.
I started using R language when MS Excel could not open the big data files. Using basic statistics knowledge and R code I developed few algorithms to identify certain patterns in the data which worked for many applications. But I still lack serious programming skills in R.
Now, I am familiar with basic inferential statistics and R packages (plyr, dplyr, ggplot2, etc). Recently I came to know that Machine Learning algorithms also help in defining patterns in the data through supervised/ unsupervised learning and their application might improve the accuracy of prediction of certain 'behaviors' of drivers using the traffic data.
Having the basic knowledge of Statistics and R, I want to learn about the data science/ machine learning as a beginner. I know that some concepts in Stats. and ML overlap and that might bridge the gap in my learning of ML. Keeping my background in mind, what resources (books/ online courses) would you recommend me to start learning data science and apply it in my field?