I just finished the immersive Data Science bootcamp by Logit on Friday and am still slowly recuperating from the experience. The course was intense – it was a firehose of material, and a rapid survey of 2 years worth of material at a Master’s level compressed into 12 weeks.
The course started with a tour of vanilla Python and the Data Science related packages (Numpy, Scipy, Pandas, Matplotlib, Seaborn, Scikit-Learn, statstools, and many more), and then covered basic statistics and probability, before going into Machine Learning, which was the main part of the course. Both unsupervised and supervised models were covered, as well as the major methods of regression, classification, and clustering (e.g. K-Means, K-Nearest Neighbors, SVM, Naive Bayes, Decision Trees and Random Forest). Regularization, resampling, and feature selection were also covered, as well as transformation (e.g. PCA). After making a simple midterm project to do an analysis of a publicly available data set (I chose to work with the Boston Housing Dataset), we moved on to Neural Networks, Time-series analysis, Natural Language Processing, and “Big Data”. As usual, if you are curious about the course materials, I’ll be uploading some of the assignments on my github.
As I mentioned above, this course was really tough. The fact that I was also commuting 2 hours each way did not make it any easier, either. It was my first time ever taking a formal class in any kind of programming or computer science – my only regret now is that I wish I had started studying this sooner! Even if I do not end up in a Data Science-related job, these skills are nonetheless enormously useful.
Now that the course is done, I’m back to where I was 3 months ago – unemployed and back on the job hunt. I’m scheduled to meet with a recruiter today, so hopefully something good pans out! Let’s hope. My goal is to hopefully get a job in the intersection of this and chemistry – ideally in cheminformatics, or using Machine Learning models in drug discovery. Even Analytical chemistry positions would not be too bad – these programmatic data analysis methods can be readily applied in that area too. If that does not work out, then I’m considering applying to Master’s programs in CS. This is a really fascinating field, and I would like to get a better foundation in this area.
But yea, now that the course is done, there will be more posts here! Watch this space…