Ways to Improve Data Science Skills in 2021
You might have seen numerous videos stating ‘Know data science in 5 minutes.’ Well, if it was that easy, everyone would have been a scientist now.
The science we have today was not there yesterday! It’s a fast-evolving field! Studying for 3–4 years at a stretch to acquire a position in an MNC, and retire with gratuity funds in hand situation is no more there in any field, leave behind data science.
The advancements are continuous. We need to speed up our learning process too. With reference to data science, the advancement in data science has made business more logical than ever before. Business leaders today are more rational and data-driven. Most businesses are actively gathering data massively from various sources such as social media, websites, the Internet of Things, and mobile. To derive insights from these massive data, they are in need of skilled data scientists and their search has increased exponentially.
Undeniably, a career in data science is lucrative and rewarding but is challenging too. Data scientists cannot be experts in one theme or one industry or one subject matter. It’s a mandate or a necessity to possess multiple skills to stay on top. They should have knowledge in the business domain and understand critical problems, have coding skills, data visualization, machine learning, and more.
Moreover, the coronavirus pandemic has thrown different challenges. Many industries have shifted to work from home culture, where employees sit at their homes and complete jobs remotely.
Though it is a great chance to use the time efficiently by reading and learning more, personal interaction, and practical exposure might be a hurdle. However, let’s understand to use the available opportunity in its course to improve data science skills.
How to improve data science skills in 2021
As a data scientist, one should have a clear understanding about the business case, should be able to chart a hypothesis, observe the trends, give details to minute things, possess numerical and analytical skills, gain working knowledge in machine learning and natural language processing.
Brush up your basic skills
It may sound astonishing. But it’s true. Many times, we tend to forget the basics or some knowledge that we learned. Because we concentrate more on the industry we are working in currently, and some of the skills/knowledge might not be put in use at that moment there.
The skills/knowledge we earned the hard way might have gone lost in the memory. Let it not be so in your case. Have a stronghold in all the basics you learned all the time. It will work when something changes in your organization, or you change your job. You will not be put in an embarrassing situation to start from scratch again.
Learn a new data science skill through an online certification
You might be learning new things constantly. There is no doubt about it. Yet, it is necessary to stay informed about the skills and processes, the industry tags related to them. The data science industry is ever-evolving, and you should match your knowledge pace with it.
Though it may take some weeks/months from you, the investment is worth it. Plan for an online data science certification. Browse the internet for top data science certifications. Also, visit the parent site of any certification you come across in a blog/article or your friend/colleague speaks of. Take a note of its syllabus and match it with the latest things you wanted to learn and know more.
Register for it, learn it, attend the exam, and it’s done. You are a certified data science professional now. It carries value when you look for other jobs or might help you to get promoted in your organization from the existing position, or make your present work easier.
It can also be LinkedIn learning, some free courses, whatever suits you. Also, read some new books related to data science available in the market. Some of the noteworthy books from beginners and intermediate professionals’ point of view include:
· Probability and Statistics for Programmers by Allen B.
· Data Science from Scratch by Joel Grus
· Python for Data Analysis by Wes McKinney
· Deep Learning with Python by Francois Cholet
Never stop learning
You might have reached a pleasant and comfortable position in your organization. That does not mean, you can stop learning or growing. Build your own project, work for side projects that interest you, and gives you more exposure. Get acquainted with new tools that you are not working but have theoretical knowledge of.
Additional projects help you to improve technical skills and show your potential recruiters that you can manage time, are open to new learning, and understand your passion for the subject.
Conclusion:
Easy, isn’t it?
Where there is a will, there is a way! The data science journey is continuous and every day is the best day to learn something.
