Transition From Non IT to IT
Switching your career from a non-IT profession to data science can be challenging. You might face fear common among Non-IT professionals such as
- Can a non-IT student like me do data science?
- Can I learn data science in a couple of months?
- Do I need to learn coding to become a data analyst? And much more
This blog will answer all your questions, from the challenges you may encounter to overcoming those fears and succeeding in data science.
Fear/Challenges non IT Professionals Face when Entering the Data Science Field
No Coding Knowledge
There are many professionals out there who still think that they can’t switch their careers to data science because they don’t have coding skills.
What if I say you don’t need coding to get into the data science field? All you need to learn Python programming language and its libraries.
Let’s understand this with an example by comparing coding in general with Python programming:
Program to calculate the average of a list of numbers.
In coding, you will use a language like C++ or Java.
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This code uses concepts like data types, loops, and arithmetic operations. It might be difficult for non-IT professionals to learn immediately.
However, in Python programming, the code will be:
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As you can see in Python, the code is much easier and simpler. Plus, the syntax is closer to human language, making it easier to understand for non-IT professionals.
Lack of Resources and Guidance
Most learners face difficulty in finding the best books or guidance on where to start, what to learn, and what not to learn.
Finding resources on your own can be challenging and time-consuming. Also, it delays the learning process.
If you are thinking that you can check out YouTube or Google, you will find a lot of videos and guidance. However, you will end up collecting a lot of both required and unnecessary information.
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Fear of Career Change
I have met many professionals from various backgrounds, including commerce, mechanical engineering, health, cybersecurity, etc. They often ask me questions about career transitioning, and two common ones are listed below:
“Is Data Science easy to learn from starting for Non-IT professionals?”
“Do I need to learn coding?”
Landing a Data Science Job without an IT Background
Finding your first data science job might be difficult due to your diverse educational background. This fear diminishes the confidence of non-IT professionals and increases their worries.
As a result:
- There is a lack of confidence, which hinders the effective showcasing of their skills.
- Career advancement is limited due to the fear of rejection when applying for data science job roles.
- Fear also hampers the learning process, which is essential for non-IT professionals to progress in the field of data science.
- Additionally, it negatively impacts productivity and decision-making in data science tasks.
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Steps You Should Take To Overcome Your Fear of non-IT Professionals
Now, it’s time to take action because it’s better to act than just to think.
Here are the points to follow:
Learning Mindset (Let the Learning Fear Go Away)
When you want to start something new, learning takes the first step. The same applies in the field of data science.
The best way to make learning long-lasting is:
- Read and give your full attention to what a mentor is explaining.
- Note down the important points either in your notebook or notepad.
- After class, review those points. If it’s theoretical, revise it; but if it’s practical, open your laptop/PC and start practicing.
- If you have any doubts, seek answers from your mentor.
Likewise, don’t be afraid to learn something new. You wanted to learn it, so you did. Therefore, always have a mindset of continuous learning. It will help you stay updated with the latest information in the data science field.
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Learning + Practise Makes Perfect
The best way to conquer data science fears is to learn and then practice. Learning helps you to practice and to understand where you need to improve and where you are really good.
Let’s understand this with an example.
If I ask you, when did you learn to ride a bike or a scooter for the first time? Did you learn first and then try when to press the clutch, brake, or increase the speed?
Well, you would say, ‘Yes.’
The reason is basic: you learned it first, and then you practiced, which helped you remember it for a long time.
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Get Free Guidance in Less than 1 Minute
If you don’t know where to start or what to learn, I would suggest booking a free consultation at any institute. Ask as many questions as you have from the counselor. This will give you clarity on what is important to learn, an idea of how many months it would take, and much more for a specific data science role.
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Career Change Means Upgrading Your Career
Changing your career simply means you are ready to upskill.
For example, imagine you are working in the health sector as an assistant. An interview comes up for a data analyst position requiring programming skills and knowledge of the health department.
If you have developed excellent data analysis skills, you can transition into this new role without changing your career but rather shifting to a different job role within the same field.
Get Your First Data Science Job
Getting your first data science job can be time-consuming but not impossible. Entering the data science field opens up multiple roles based on your skills.
However, to get your dream job, you must follow these points:
- Learn Basics: Python/R programming language and its libraries.
- Work on Real-World Projects: Analyze datasets, build models, and create visualizations.
- Network: Connect with professionals, join forums, and attend events.
- Gain Experience: Seek internships, freelance, or volunteer roles.
- Customize Resume: Highlight relevant skills and projects.
- Prepare for Interviews: Practice common questions, and showcase problem-solving skills.
- Stay Persistent: Keep learning, stay flexible, and don’t give up.
Overall, overcoming the fear of entering data science from a non-IT background involves taking action. Adopt a learning mindset, practice regularly, and seek help when needed. By upskilling and leveraging existing skills, you can transition into data science roles successfully.
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