3 answers
3
Updated 410 views

How can i be a data scientist from non maths nd non computer background ?

I am in grade 12 rn having biology stream as well as a non computer student but i want to be a data scientist please tell me can i ? By learning skills from scratch nd does colleges provide BCA to non comp nd non maths students?

career-counseling computer-science datascience careerguidance stemcareer careerswitch skillup designcareerguide from-biology-to-tech learningpath
Thank you comment icon Hey Yuvika, yes you can become a Data Scientist but you need to learn new skills from the beginning like you need to learn basic maths and statistics, python programming, excel and SQL, Data Visualization and Machine Learning. For BCA admission, yes you can take BCA without computer and maths in 12 but its all depend on the college. Hope this will help you. Mamta
Answer This
3

3 answers

0
Updated
Share a link to this answer
Share a link to this answer

Chinyere’s Answer

Hi Yuvika!

Yes, even if you have a background in biology, you can work as a data scientist. Many great data scientists actually began their careers in the life sciences, psychology, or economics, disciplines that develop curiosity and critical thinking long before code is involved.

Here’s how to bridge the gap:
- Start with the basics: Online platforms such as Coursera, Kaggle, and free YouTube lessons are great places to start learning Python, Excel, and statistics. You don't immediately require a strong foundation in arithmetic; you'll learn the necessary skills gradually.

- Build comfort with numbers: Focus on applied math, areas like probability, data visualization, and linear algebra as you go. It is more important to understand patterns than to commit formulas to memory.

- Pick a data-related degree or pathway: Students without a background in arithmetic or computers are allowed to enroll in BCA, BSc Data Science, or similar programs at several universities. All you have to do is review each college's qualifying requirements; some offer foundation courses, while others require math.

- Create a small project portfolio: Analyze public data; if biology or health databases are your area of expertise, you might want to do so. It will strengthen your transition strategy.

You can surely transition from "bio student" to "data scientist" if you maintain consistency. It doesn't matter where you begin; what matters is how you teach your brain to think with facts. You already possess curiosity, which completes half of the task.

Best wishes!
0
0
Updated
Share a link to this answer
Share a link to this answer

Jacob’s Answer

So the basis of pretty much all data science is rooted in mathematics. That doesn't mean you need to have a math degree but you do need to have a firm grasp of the foundations of statistics and probability. Starting to familiarize yourself with that math is a good jumping off point. From there you will want to start to learn the languages/means to interact with the data. SQL is essential for dealing with databases to get and shape the data you work with. R and Python are commonly leveraged for data science for data shaping and model development. Learning either of these will allow you to more broadly dive into the work you want to pursue.
0
0
Updated
Share a link to this answer
Share a link to this answer

Arun’s Answer

That's a great question. Based on my personal experience, I also had a biology stream in school and initially had little idea about computers and software. Back then, we didn't have many open sources to learn from, but I gradually taught myself about technology and computers. I've now been working in the IT field for almost 15 years, during which I've learned a lot and continue to learn new technologies. Currently, you can check platforms like YouTube, Udemy, or Coursera for guidance on how to start from scratch and become proficient. Additionally, leverage OpenAI or Gemini (responsibly) to learn about data, and you can definitely become a data scientist at your own pace and based on your pattern of learning.

Arun recommends the following next steps:

Getting through youtube basic videos
Leveraging the Open AI tools
0