How to Position Yourself as a Data Scientist Before Turning 35
If you're aspiring to become a data scientist by the age of 35, it's essential to take the right steps starting now. Based on my experience, especially in India, these strategies can help you gain the necessary skills and network to achieve your goal.
1. Complete the Machine Learning Course by Andrew Ng on Coursera
The Machine Learning course by Andrew Ng on Coursera is a must-take course. It provides a comprehensive overview of ML algorithms and is a solid foundation for your data science journey. This course is widely respected and will give you a competitive edge.
2. Participate in Kaggle Contests
Regularly participate in Kaggle competitions. Pick contests with a good number of participants and submit your solutions every day. Engage with the forums to understand what other contestants are doing to improve their scores. This hands-on experience is invaluable and will prepare you for real-world projects.
3. Master a Programming Language for Data Science
Pick up R or Python and implement some of the machine learning algorithms you learned in the Coursera course. For R, consider books like R Cookbook and R in a Nutshell. The Data Science specialization course from Johns Hopkins University on Coursera also provides a great introduction to R.
4. Attend Data Science and Machine Learning Meetups
Join and attend data science and machine learning interest group meetings. These meetups in cities like Chennai are a mix of students and industry thought leaders. They are excellent networking opportunities to connect with professionals and discover job openings in the data science field.
5. Utilize LinkedIn to Seek Job Opportunities
Analyze the companies you are interested in and connect with founders and managers on LinkedIn. Send personalized messages to introduce yourself, express your aspiration to join their company, and discuss how you can quickly become proficient in the domain.
Certifications
Certifications from MOOCs like Coursera and edX can keep you motivated, but they may not be the deciding factor in landing a job. However, certifications in Hadoop and Spark from Databricks can significantly enhance your credibility.
Considering a PhD
While it's not necessary to pursue a PhD immediately, once you gain around 3-4 years of experience, you might consider this advanced degree. A PhD can be very beneficial if you're interested in conducting in-depth research in a specific area of data science.
By following these steps, you'll be well on your way to becoming a successful data scientist before turning 35. Start now and stay persistent in your journey.