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Giving up Data Science?                

Data Science is extremely complicated and toll taking. Though switching to another career is always hard. I  have had times where I wanted to give up after rejections.  Here are few tips to get ahead in the game doesn't matter how many rejections you have faced.

1- Always be prepaid for the major topics in Data Science 

Usually, employers are more concerned about your basics than complex queries. Probability and applied statistics are a must and can be refreshed by your basic school-level knowledge of statistics. Make sure you are well versed with modelling for this you can visit information blogs dedicated to Machine Learning, for example, Analyticsvidhya has the best informative blogs.

2-Make your projects visible online

Posting your work on the online community not only helps you and make your skills visible but also helps new aspirants. Git hub is important if you are thinking of making your career in Data Science. Work on maximum online data sets and make sure your work shows variety.

3-Understanding differences in job descriptions

Beginners are always confused about which job descriptions are best for their skills. There are data analysts, data engineers, business analysts, business intelligence managers and data scientists. You need to analyse and make sure you have a long term plan before stepping into any position. Many professionals have blogs explaining the industry and their expectations but the best is to connect with people on Linked In.

4- Connect with people on social media

Make sure you reach out to people on Linked In with similar skills as of you and a career that you aspire to have. Filter people according to the company you are interested in > click on the profile who has the job position that you desire> check his skills, projects and certifications> send a customized message and wait for their response. Most people on Linked In are happy to help.

5- Keep going

keep hustling and don't lose hope. Connect with people with similar interests online and don't leave projects in the middle if you run into problems. Take help of Stack overflow, Kaggle, Github. there is only one way of learning to code i.e keep doing it. Select open-source data sets from Data.world, Kaggle.com, government census website and archive.ics.uci.edu etc.

Last but not least is that learning takes time and a lot of patience. so keep your hopes up and resumes ready.  If you feel like this article helped you and you want to know more about my ongoing journey. Please comment below. Follow my blog for more Data related quests.


-DataDevil

Honey Saini


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