Seattle
my two internships.
When I was in college, I did 2 internships at Microsoft.
The first was a data science Internship in San Francisco, and the second was an internship at Seattle's product manager position.
In this episode, I'll focus on sharing the first Data science internship I've got.
In case you're not familiar with data science, in short, it's a combination of computer science and statistical mathematics. Skills
So before I share how to get the job, I believe that getting a perfect job is actually just a formula. First, you need to master your skills. Data structures and algorithms
The first thing I did to get this data science job was to take some programming lessons. Includes basic programming, data structures and algorithms.
Using the algorithms of the courses I learned, I finally got my first technical internship. It was an intern at a small software development company in Beijing. While I was practicing, I began to study some very interesting math problems. Self-directed learning and practical projects
After that, I also spent a few months studying statistical math courses, because this is my major.
Then I started to collect my machine learning program from the California Institute of Technology on the Internet. The resources of these courses, you can visit Unreal School, correspond to our program, get links to tutorials.
Machine Learning Courses
So, using the knowledge I learned from these courses, I started to practice some machine learning projects on a website called Kaggle. Kaggle, a Web site founded in Melbourne in 2010, provides a platform for developers and data scientists to host machine learning contests, host databases, and write and share code. The platform has attracted the attention of a lot of data scientists, the resources of these users are the main factors that attract me.
Kaggle
Comprehensive capabilities
So, having done all this preparation, when I applied for Microsoft's data science position, I believed that I was able to stand out from my statistical math major, my programming experience, and the comprehensive capabilities of the machine learning project.
This comprehensive accumulation of knowledge may be not available on the resume of any other candidate. Interview questions
There are two main types of questions in the interview for data Science jobs in San Francisco.
One of the problems is to solve mathematical problems, some mathematics problems mainly focus on the probability, others focus on combinatorial learning. 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 required are not because I want to find a job in data science, but mainly because I really enjoy the process of practicing machine learning projects.
I know that these projects are at some point, to some extent, helpful in getting a job.
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 satisfactory job, as I have just said
In addition to having skills, you also need to have 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 about the idea, and then one day she told me there was a lecture, a lecturer from Microsoft explaining how the data was used in science and statistics.
So I took this 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 the process of how I get the interview opportunity.
Like mastering skills, I want to participate in data science related activities not just because I want to put it on my resume. It's because I want to keep this information connected so I can get a job opportunity. This is where I feel the meaning. Summary
The
concludes that, first of all, I believe that the combination of formal education and practical experience with individual projects is the core competitiveness.
in my personal experience, I taught myself the statistics course, had a project internship experience, and then had my own math and machine learning related projects, all contributed to my first internship at Microsoft.
Then, my second experience is: I think you should enjoy the process of building your own skills and connecting information, and if you are interested in it, it will be easier to master these skills.
OK, this is the entire content of the Geek Programmer's chopping road, and we share our learning goals and work planning knowledge. I hope you can find a good internship or work.
Finally, if you want to hear more free dry audio programs, like and subscribe to our program. We'll see you next time.