I am planning to apply for MS in Data Science in 2020. What can I do to improve my profile in the next one year?
I have a bachelor’s instrumentation and Control Engineering, graduated in 2018. I am working in the IOT domain on Machine learning projects. What can I do, apart from the work experience, to improve my profile to get top colleges?
4 answers
Satish’s Answer
Swetha , Congratulations on your graduation. Data Science is one of the key demanding profiles in the industry today, companies constantly look for people who can talk to Data and share insights and tell the story using data. As a first step to strengthen your skills and prepare for the learning - Working as an intern on Data Science areas would be beneficial, if you have not started it already. Find a mentor who can give you real life situations and problems, work on real time case studies. Challenges you see in real world are much different and sometimes involves applying your leanings on Data science + Interpersonal skills. Connect with other experts in the industry of interest . Ask a Data scientist or a Student who have completed a Data science course, Prepare a milestone checklist and start accomplishing them with a plan to be ready for 2020!
Benjamin’s Answer
Below are some high-level examples of things that many colleges look for in applicants to MS programs in Data Science:
- Define your career aspirations and articulate the alignment of your passion to the program to which you plan to apply. This goes a long way toward preparing yourself for written or in-person interviews where you'll likely need to answer this question.
- Verify your Bachelor's degree includes all of the prerequisite coursework to get into the MS program.
- Continuously develop your programming skills (e.g. R, Python, others). If the MS program is oriented toward any particular programming language, then build your skills.
- Be sure your undergraduate coursework, project-work, and any related jobs can be used to demonstrate strong knowledge of complex techniques used in Data Science for analysis of data. Your academic success in specific coursework will help. Projects or jobs where you can prove you've successfully applied the techniques will be an even bigger help.
- Data Science as a discipline requires substantial collaboration and teamwork. You will want to demonstrate that you are a strong team player with real examples.
- Throughout the application process, you'll likely be evaluated for maturity and professionalism -- including leadership ability. Find opportunities to lead and manage a data project -- you'll learn a lot about yourself and prepare for a future in Data Science.
Best of Luck!
Jimmy’s Answer
In my experience and discussions with the best people in the industry, it is important to have strong technical skills. I would recommend building up expertise in SQL and Python. SQL skills are necessary to acquire, manipulate, and aggregate data from enterprise systems. Python is a multi-purpose language that is growing in popularity for Data Science. It is often used to run machine learning and statistical testing. It can also be useful to gain expertise in a data visualization tool like Tableau or PowerBI. Python or R can also be used for data visualization.
When applying to school or a job, they will likely ask about your previous project experience. One way to get this experience is by participating in Kaggle competitions (https://www.kaggle.com/competitions)
Best of luck!
Arundeep’s Answer
It really depends on which section of your profile which would add most value. Since the primary intent is to get admission into the top colleges, I would suggest in broadening your profile. To add more into the Technical depth, you could pursue certifications in the specified domain. For example, there's Stanford's Machine Learning Course / Data Science Bootcamp etc, that can boost your profile. Attaining the certification would be an icing on the cake along with your experience on IoT products.
You should also possibly consider connecting to alumni folks from the top universities that you have in mind for their inputs on the Data Science specialization that you plan to take up.
A lot of Ivy League universities look into the things you have done above and beyond your current scope. It could include mentoring the current knowledge of Machine Learning that you possess through career experience / working on new initiatives within your company and also entering open challenges / online hackathons to showcase the best of your ability. This can add tremendous value to your current scope of work.