How To Get A Phd In Machine Learning While Having An Online Degree

I entered the heated university debate over “being a liberal” on the California Supreme Court this week. What was it really like to be a student there?

There’s a reason you shouldn’t do your thesis paper in 10 minutes. Here’s how to complete it on your terms:

I don’t think there’s any doubt that, for some brilliant self-professed thinkers, the scientific method has undergone its greatest and most transparent adaptation and pilfering. You can spend hours talking to a bunch of smart people, and there is no question that you’ll learn a lot. But sometimes it feels like there are few limits to how much you can learn.

My current project is a Ph.D. in Machine Learning, the field of artificial intelligence that often uses statistics to quickly convert data into insights. I earned a bachelor’s degree in computer science by taking advantage of a number of nifty online courses that can train you to be a scientist within the time you’d normally spend attending a full-time Ph.D. program. But I’ve since learned that I don’t have a pre-requisite for a Ph.D. (besides smarts), and I’m making the most of that before I cross the other side.

Here’s how I did it.

I spoke to super smart people. I figured out what the weird robot thing means. I gathered statistics data. I did it all at a top 10 site with thousands of papers written by both experts and novices.

If you don’t have a pre-requisite for a Ph.D., what you need to have in your back pocket is an understanding of any field of research, from physics to bioinformatics to biological systems. Some languages and math may even be helpful. Before I decided to major in computer science, I majored in English, wanting to be a journalist. I also learned different languages and got into computer programming. To be fair, computer science was the direction I eventually went because I believed it would lead to better paying gigs in my field. But the science was the driving force for me, and going to college with a STEM background made studying it even easier.

Early on, my advisor told me to stop worrying about enrollment numbers. I don’t want to be stressed about this. My grade will take care of itself. At the beginning of each quarter, she presented me with two brochures: one that said “We Don’t Have a Class,” and one that said “We Have a CLASS.” She explained that even if our average load decreased each quarter, our average load would increase and that we’d just be regressing from a high point the first quarter. And that’s exactly what happened. Having this level of control over my cohort definitely helped me achieve a much higher GPA at the end of the semester.

I met a bunch of fun and crazy nerds. I had a lot of fun with my Ph.D. advisors: figuring out how to host meetings at fancy places, planning field trips and hands-on projects, and preparing projects. If you need some advice, you should talk to other Ph.D.s or have an advisor help you out. It’s great to mentor young people. We’re the ones on the front lines of the field; we should support the next generation who are excited and passionate about their field.

I did all of this during the summer before the quarter and toward the end of the semester. This gave me a lot of extra time to focus on completing the Ph.D. I was also able to master machine learning without taking as many classes. The courses I took were difficult enough that I was able to pick them apart while sitting at my desk by myself. I didn’t want any of them to be too difficult because I knew I could graduate in under three years.

Not having to take courses at night allowed me to miss work when I needed to but still get assignments done on time. This kept me on track.

Ultimately, the class that taught me the most about machine learning was a free course I took on FitStar. I actually had fun with it. It’s pretty basic, but it teaches you to put your statistics data together with some other numbers and extrapolate those out. One of the things that you learn is that if you’re trying to learn about something other than your area of interest, you have to start with simple things. If you start with that, you can learn a lot from basic math courses and from free online courses.

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