The 1st 1 was a data science inter ship in San Francisco, and the second alone was a program manager internship in Redman, which is near Seattle.

In this video, I'm going to focus on how I got my first internship there as that they're scientists, just in case you're not familiar with it.

Their science is sort of a combination between computer science on statistics or their analysis.

But before I go into how I got the job, I believe that there is a formula for getting a great job.

It's in the form off something plus something else.

The 1st 1 of these is skills.

The first thing I did for building my skill set for this particular data science position was I took a few programming courses.

There were on basic programming and data structures on algorithms.

Using what I learned in those courses, I eventually landed my first technical internship.

That one was as a software developer intern at a tiny startup in Tokyo.

When I was working there, I also started working on some competitive math problems just for fun.

After that, I took a few statistics courses because it was my measure.

I also started learning machine learning on my own by taking an online course from California Institute of Technology, which is also known as Celtic.

Using what I learned from those courses, I started working on a few must relearning projects using a website called Chicago.

So how did all of these come together?

When I applied for the data science position at Microsoft, I believe what made me stand out was the combination off my statistics background, my programming experience as well as the machine learning project I put on my resume.

It was probably rare for any other candidate to have a combination off all of those things at the same time on their resume.

And as for the interviews for this data science position in San Francisco, there were two types of questions.

One of them was solving math problems.

Some of these math problems were focused on probabilities, while others were focused on other areas of math.

For example, community oryx.

I was actually well prepared for this type of questions because of my experience with competitive mouth problems, which I mentioned earlier.

The other type of questions was statistics and their analysis related questions For these questions, I found that taking a few statistics courses of my university on working on a few machine learning related personal projects was really helpful.

So the reason I worked on those particular skills was not just because I wanted to get a job in data science.

It was mostly because I genuinely enjoyed working on each of those projects.

I sort of knew that statistics would be used for for getting a job at some point somehow.

And I also knew that fundamental mass skills are good to have because they're universally applicable.

But I didn't expect them to be useful in this specific way.

All right, let's go back to the form that I mentioned earlier for getting a great job.

As I said earlier, the formula is getting a great job is equal to skills, plus something else.

In my opinion, this something else is connections.

So right before I apply to the data science position, I was actually trying to start a data science club at my university, so I was talking to a statistics professor about it.

On one day she told me about an event in which a speaker from Microsoft would talk about how data science and statistics were being used there.

So I went to the event on Afterwards, I asked the speaker there if Microsoft was hiring any data.

Science interns, he said Yes.

So I sent in my resume later, and that's how I got a need to be with them, just like how I built my skills.

The reason I wanted to start their science club wasn't just because I wanted to put it on my resume or because I wanted to build connections so I could get a job one day.

It was just because it was something I wanted to do because I found a meaningful.

So what's a key takeaway here?

First of all, I believe that a combination off formal education, practical experience and personal projects can be really powerful.

In my particular case, taking a few statistics courses of my university, having done one programming inter ship on working on math, on machine learning, personal projects all contributed to eventually getting my first internship of Microsoft on the second take away from my personal experience here is that I think you should build your skills on the collections in a way, you enjoy the process a lot.

If you enjoy the process, you will want to spend more time on those things.

So it should become easier for you to build those skills and connections.

Let me know when you do it.

All right.

That's all I have for this video.

Good luck, guys on getting your next job or internship.

And if you want more videos like this, like this video on sub sky for more on, I'll see in the next video.