Data Science Career: Eligibility & Degree Requirements – NDMIT

Anyone can learn data science with dedication, a structured approach, and a willingness to acquire the necessary skills. —whether you’re a student, working professional, or entrepreneur—because it’s one of the most in-demand skills in today’s job market, offering high-paying career opportunities worldwide.

Here’s who can join:

●Undergraduate – 10+2 (any stream) with Mathematics or Computer Science.

●Postgraduate – Bachelor’s degree in STEM (Science, Technology, Engineering, Mathematics) or Business, with at least 50–60% marks.

●Certifications – Open to anyone with basic computer literacy and a desire to learn.

NDMIT’s Data Science Courses:

● Certified Data Analyst – 3 Months

● Certified Data Scientist-ML Track – 6 Months

● Certified Data Scientist-AI Course – 10 Months

No matter your background, you can start your journey today and move toward a high-demand, high-paying career in data science and AI

Is a Degree Mandatory?

● Corporate & Research Jobs: A degree can be an advantage.

● Industry & Startup Roles: Skills and projects often matter more than degrees.

Why Skills Matter More

● Strong portfolios- Kaggle competition experience

● Real-world project exposure

Key Skills Before Applying (We will provide this also)

1. Statistics & Probability
2. Python or R
3. Machine Learning basics
4. SQL & database management
5. Data visualization (Tableau, Power BI)

Conclusion

At NDMIT, we prepare students for both degree-based and skills-based career paths in DataScience—so whichever route you choose, you’re future-ready.

Frequently asked question

1. What is the minimum educational qualification required for a career in data science?

Most data science programs require candidates to have at least a bachelor’s degree in a relevant field such as Computer Science, Mathematics, Statistics, Engineering, or Economics. However, many institutes and NDMIT online platforms now offer beginner-friendly courses for graduates from any discipline, as long as they have an interest in analytical thinking and problem-solving.

2. Do I need to have prior programming knowledge to pursue data science?

While prior programming experience in languages like Python, R, or SQL can be beneficial, it is not always mandatory—especially for beginner-level courses. Many institutes start with foundational programming lessons. However, NDMIT also provide learning of data science and analytics from scratch to advanced programs, because a basic understanding of programming is usually recommended.

3. Are there any specific skills required before enrolling in a data science course?

Yes, having a grasp of mathematics, statistics, logical reasoning, and analytical thinking is highly valuable. Problem-solving ability, familiarity with data visualization tools, and curiosity for uncovering insights from data are also important. Technical skills can be developed during the course, but an analytical mindset is a must.

4. Can working professionals from non-technical backgrounds apply for data science programs?

Absolutely. Many data science programs are designed for career switchers. Professionals from finance, marketing, healthcare, and other fields can transition into data science by learning relevant tools and methods. Institutes often provide bridge courses or preparatory modules to help non-technical learners get up to speed.

5. Is a master’s degree necessary to become a data scientist?

No, a master’s degree is not mandatory to enter the field. Many successful data scientists have started their careers after completing a diploma, certification course, or bootcamp. However, a master’s degree in Data Science, AI, or a related field can provide deeper knowledge, research opportunities, and an advantage for higher-level positions.