Hello everyone, I'm a materials engineering student who will soon be graduating but I want to work with machine learning/data analisys in the future.
My university course didn't have anything on these topics, but I studied them through online courses on Coursera/EDX, most notably these:
https://www.coursera.org/course/ml
https://www.coursera.org/specialization/jhudatascience/1?utm_medium=dashboard
https://courses.edx.org/courses/MITx/15.071x/1T2014/info
However, I still don't feel that I know enough about the topic to say that I could work in the area and all my knowledge is way too basic. How should I proceed to become better? I could think of these options:
Buying some books and doing everything on them. I was thinking about: "Machine Learning for Hackers" and "Programming Collective Intelligence: Building Smart Web 2.0 Applications". I still don't have any book, so buying them would at least give me somewhere to consult.
Applying for a Master's program. However, I'm not american or I'm in the US. I know it is a longshot, but does anyone know someone who is very good in the area in Brazil? I'm gratuating from one of the best engineering schools here so it wouldn't be a problem to get a masters here. If I have to go to the US (or other country), do you have any advice?
Kaggle competitions. I've never done any of those, but some of them seem kinda hard, especially if you are aiming to get a good place on them. What would be a good one for a first timer?
Doing more online courses. I've looked into Udacity and they seem to also have some very good courses like Intro to Data Science, Intro to Hadoop and MapReduce, Data Analysis with R, Machine Learning: Supervised Learning and many others.
What do you think, which way is better? Or maybe a combination? Do you have any suggestions?
At last, it seems a lot of you work on related fields, how did you get to work with Machine Learning? What is the best way to get into the field?
Thanks for all the help, guys.
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