Starting your data science career maybe a bit terrifying. But, with the right data science career path, you can do great wonders.
At Edugrad, we train freshers and experienced professionals who want to switch their careers in the most cutting-edge technology and help them get their dream careers. Here, in this article, we will be talking about the ideal data science career path that you can undertake to ensure that you have a fantastic start to your data science career.
Identify your goals and match them with the data science jobs profile –
First, let us start with the obvious. Your motives. It is important to identify the data science jobs for freshers that are in demand in the data science sector and then focus your efforts to ace the interview.
Data Science is a huge field in itself and there are myriad data science jobs that are present for people with different skillsets.
This is why you ought to talk with your friends and experienced professionals in the space and ask them about their personal experience working in data science. If you are not exactly a people-person, then you can explore myriad data science communities such as Kaggle, Quora and relevant subreddits where people are more than willing to share useful information about the data science domain.
Subjects that a data scientist needs to be adept at:
- Math & Statistics
- Database querying
- Soft Skills
If you are someone who is very good at written communication along with an interest in programming, an NLP chatbot developer would be the perfect fit. On the other hand, if you are someone who is adept at math & programming, you can be a really good machine learning engineer.
So, at the end of the day, the process starts with identifying your goals and matching them with the right career options that might work for you.
Have the persistence to finish an online course that you started –
With the rapid proliferation of data, data science communities and learning resources are now more than ever.
There are a vast number of quality data analytics courses for professionals looking to learn data science from scratch on their own and do some data analytics projects too. Here are some valuable resources that you can check out:
If you are someone who is looking for really good courses and Industrial projects in Data Science, Machine Learning and Deep Learning, you ought to check out our platform. Our courses and projects have been designed by the ex-Google team. With good mentoring and dedicated support, Edugrad helps immensely in giving you practical knowledge because we believe in learning by doing approach.
If you are someone looking for just a quality accreditation that employers value, you ought to check Udacity out. They offer nano degrees for Master’s program in collaboration with good colleges. A course typically takes 3 to 6 months to be completed.
An online MOOC whose data science courses can offer you a basic overview of data science prerequisites like what is data science. It can be helpful for those who are newbie to this cutting-edge technology.
Interact with Data Science community –
Interact personally with the data science community. Talk with your peers on Kaggle, Reddit, Quora & StackExchange and ask them questions about their experience being a data scientist. There are folks in myriad data science communities on the web who are more than willing to share their experiences.
Your online peers would not only answer questions and enhance your technical chops but would also be very useful in myriad aspects and guide you in your journey.
If you live in a metro city, also look for offline forums where people with interests in data science usually gather.
Practice, practice, and practice –
Practical experience beats theory every time. If you are an amateur data science professional, you ought to look for projects where you can leverage your learning.
Be it fiddling with datasets on Kaggle, making an NLP chatbot for your local restaurant or deriving insights from real-life data, practice the concepts you learned, in real-time to have a better understanding of the different subjects.
There are a variety of sites online where you can gain access to open-source datasets. Solving complicated problems using the open-source data should be the way ahead.
If you are pursuing a classroom course/an online data science course, have a mentor with you by the side when you hit an obstacle.
Communicate and network –
Last but not least, a good data scientist is not only someone who is adept at data science certification but also someone who is able to visualize the data and communicate the insights to a layperson.
This is why you ought to learn the much needed visual communication tools such as:
- Power BI
And other visual communication tools that can help immensely in helping you stand out amongst your peers. Also, learning soft skills is a must for a data scientist. Remember that if you ain’t willing to step up and present up your work, you are just giving space to someone else to take credit for your work.
PS: Check out our free course on mastering presentation skills for data scientists here.
When it comes to networking, you ought to check our blog where we detail everything that ought to be done to build a data science resume that STANDS OUT!
We hope you had a good read. The roadmap for each individual is different at the end of the day. So, start on your data science journey. We are sure you would have a unique and interesting journey.