Some of the most common challenges faced by data science enthusiasts while starting their Data Science Journey are:
A lack of experience
Not knowing where to start
Unable to create networks
Unable to connect to the right people
Thus, to solve these problems I listed 30 steps to kickstart your Data Science Journey. Let’s have a look:
1. Have enough time to start learning to program you can start from basic languages like Java or C++ or directly with Python but make sure whatever you learn, learn well.
2. Read and keep reading a lot of Books, Blogs, articles, or anything that is interesting and adds up to your data science skills, just read it even if it means just reading 15 mins a day.
3. Experiment with Different learning resources be it a video playlist a course or MOOC’s, it depends on what suits you and your style of learning.
4. Start the basic training with excel. It’s easy to start with and gives a quick start to what you are willing to achieve.
5. Don’t just keep revising the theory, practice practical codes and projects.
6. Choose Python or R. But when in confusion, go with Python it is easier and highly recommended.
7. Don’t just keep revising the theory, practice practical codes and projects.
8. Practice with different data sets. Not just the basic datasets like ones from Kaggle but real-world datasets.
9. Identify your weakness and give a weekly break to analyze and work upon it.
10. Build your own datasets. For example, a GitHub user used his WhatsApp chats with his girlfriend to analyze their relationship status. Also, you can always do web scraping to create your datasets.
11. Practice the skills of explaining difficult concepts to a layman in simple terms. It’s important to have good story skills to be a Data Scientist as you may have to deal with stakeholders who have no idea what technical terms you deal with.
12. Get your mentors it could be a friend, teacher, or connect with someone on LinkedIn who can review your profile.
13. Whatever you learn write it down and publish online as a blog or an article. It helps to showcase your knowledge to the recruiters.
14. Participate in Kaggle competitions. It is an amazing platform to sharpen your skills and to connect with the right people brushing up your skills.
15. Join Data Science Groups, Events, Meetups, and anything that lets you socialize with the right people who can relate to your ideas.
16. Be socially active. You never know who might find your profile interesting and offer you a Job.
17. Keep yourself updated by reading Data Science related News it gives you an extra kick to keep the interviewer engaged.
18. Create a Linkedin along with a GitHub profile and be hyperactive. The stronger the network is stronger are the chances of being Hired.
20. Link your job with your interests so you remain passionate even while working and the job doesn’t get boring after some time.
21. Consider not just large companies but even small startups. You’ll learn more and have a perfect growth.
22. See who your competition is and what skill sets are required to achieve what you desire.
23. Prepare interview questions and brush up your communication skills.
24. Be well versed with your project and be able to talk about it in a detailed manner.
25. Bring something unique to the interview research the companies and the tools they use and how you can help grow the company through your skills.
While doing a Data Science Job
26. Keep Upskilling with a constant learning approach. Stay updated with new skills and technologies during your Data Science Journey.
27. Stay flexible. Ask questions and feedback to constantly improve. Don’t just stick with the old approach, Keep experimenting.
28. Be an amazing Storyteller by creating great visualizations to make sure your growth doesn’t stop.
29. Teach online through Youtube or create a course to spread your knowledge. You’ll be amazed by the amount of mental satisfaction it provides you.
30. Stay humble and be always ready to learn something new, by not just working on your technical skills but also the attitude you work with.
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