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Excited to see you interested in data science and machine learning. It can be a daunting space to get up and running with. I'll talk about getting up and running with data science and machine learning. For big data, you're really looking at a set of technologies (e.g. Hadoop, various AWS tools, Spark, etc). You can learn these on your own by downloading and experimenting with them, but realistically most new professional are exposed to them on the job. What's more important is learning to think about how to parallelize and scale computation tasks to take advantage of those technologies.
On the data science/ML front. First check if there are classes in statistics department around statistical learning. Regardless of whether data science/ML classes are available, you'll want to build a solid base in statistics and probability.
If offered take the following classes to help create a solid base:
- intro to statistics and probability
- bayesian inference
- linear algebra and differential equation
- Calculus I and II for machine learning
Machine learning builds on what you learn in those classes above and gives you a set of tools and techniques tackle various problems. Most machine learning engineers use the same set of software packages to get started (e.g. Python and the following python libraries: sci-kit learn, numpy, pandas, etc). The best way to learn is by doing. I'd suggest taking Udacity's Intro to Machine Learning class or following the ML tutorials on Kaggle. The Udacity class is free and provides a great application based approach to get you up and running with machine learning. Once you have a taste of the common techniques (e.g. Regression, Decision Trees, K nearest neighbors, etc) you'll want to get more real world experience with more complex problems and data sets. Kaggle provides a great source of resources here. They data science competitions where any one can participate and the top competitors can even win prizes. The competitions will give you a fantastic introduction to diverse set of problems and you'll get to see what cutting edge ML techniques are being used (hint it's almost alway XGboost lol).
Finally, talk to your career office and look for internship opportunities. Good luck!
100% of 1 Students