02 How did I get a job at Microsoft?

Seattle my two internships.

When I was in college, I did 2 internships in Microsoft.
The first was an internship at the Data Science post in San Francisco, and the second was an internship at Seattle's product manager position.
This episode, I'm going to focus on sharing my first Data science internship.
In case you are unfamiliar with data science, in short, it is a combination of computer science and statistical mathematics. Skills

So before I share how to get this job, I believe that getting a perfect job is just a formula. First, you need to master skills. Data structures and algorithms

The first thing I did to get this job as a data science job was to take some programming classes. Includes basic programming, data structures, and algorithms.
Using the algorithms I've learned in these courses, I finally got my first technical internship. It was an intern at a small software development company in Beijing. When I was an intern, I began to study some very interesting math problems. Autonomous learning and practical projects

After that, I also spent a few months studying mathematics courses, because this is my major.
Then I started to collect my computer courses at Caltech on the Internet. The resources of these courses, you can visit the Unreal Private school, correspond to our program, get links to tutorials.

Machine Learning Course

So, using the knowledge I learned from these courses, I started to practice some machine learning projects on a website called Kaggle. Kaggle is a website founded in Melbourne in 2010, which provides developers and data scientists with a platform for organizing machine learning competitions, hosting databases, writing and sharing code. The platform has attracted the attention of many data scientists, and the resources of these users are the main factors that attract me.

Kaggle

Comprehensive ability

So, after all this preparation, when I applied for Microsoft's data science position, I was convinced that I was able to stand out from my statistical math major, my programming experience, and the comprehensive capabilities of the machine learning program.
This combined accumulation of knowledge may not be available on the resume of any other candidate. Interview questions

There are two main types of questions in the San Francisco data Science job interview.
One of the problems is to solve the mathematical problems, some mathematical problems are mainly in probability, others focus on combinatorics. I
In fact, very good preparation of this type of problem, after all, my major is this.
Another type is data analysis-related issues. For this type of problem, it will be very helpful to practice some machine learning related projects.
The skills needed are not because I'm looking for a job in data science, but mostly because I really enjoy the process of practicing machine learning projects.
I know that these projects are helpful in getting a job at some point and in some ways.
I also know that basic math skills are worth learning because they are universally applicable. ability to link information

So, let's go back to the formula mentioned earlier,
Want to get a satisfying job as I have just said
In addition to the skills required, there is also the ability to link information.
Before I started applying for this position, I also tried to participate in some data science activities during college.
So I told my statistics professor, and then one day, she told me there was a lecture about how data is used in science and statistics, by a lecturer from Microsoft.
So I took part in the lecture, and then I asked the lecturer if Microsoft had hired a data science intern, and he said yes, so I sent him my detailed resume.
This is how I got the interview opportunity process.
Like mastering skills, I want to participate in data science related activities not just because I want to put it on my resume. But because I want to keep the connection with this information so that I can get a job opportunity. That's where I feel like it makes sense. Summary

To sum up, first of all I think that the combination of formal education and practical experience and personal projects is the core of competitiveness.
in my personal experience, self-study statistics courses, have a project internship experience, and then, have their own math and machine learning related projects, all contributed to my first internship at Microsoft.
Then, my second experience is that I think you should enjoy the process of building your own skills and connecting to information that will naturally be easier to master if you are interested in it.
OK, this is the entire content of this issue of the geek programmer chopping Road, we share the learning objectives and work planning knowledge. I hope you can find a good internship or a job.
Finally, if you want to hear more free dry-goods audio programs, click on the praise and subscribe to our program. We'll see you next time.