data science for Non-Technical background

How to get into Data Science from Non-Technical Background?

Data Science has emerged as one of the most prominent and demanding prospects in the with millions of job roles coming up in the market. Pursuing a career in Data Science can be highly promising and you can become a Data Science even without having prior knowledge on technical concepts.

There are several courses on Data Science for Non-Technical background aspirants ensuring that they can develop their skills and capabilities to become a Data Scientist. Let’s read the blog to know how can a non-technical person learn Data Science.

Required Data Science Skills:

As a Data Science aspirant willing to opt for a Data Science course for non-IT background, you need to know the technical and non-technical skills you require to become a Data Scientist. Following are the technical and non-technical skills you require to become a Data Scientist:

Technical Skills:

Non-Technical Skills:

  •   Strong business Acumen
  •   Excellent communication skills
  •   Analytical Mindset
  •   Critical Thinking
  •   Decision Making
  •   Data Intuition 

How to become a Data Scientist with a non-technical background?

Becoming a data scientist with a non-technical background is indeed possible, although it may require some additional effort and dedication. Here are some steps you can take to transition into a data science career:

  • Develop a solid foundation in mathematics and statistics: Data science heavily relies on mathematical concepts and statistical analysis. Take the time to brush up on these subjects, either through online courses, textbooks, or even formal education if feasible.
  • Learn programming languages and tools: While you may not have a technical background, acquiring programming skills is essential in data science. Start by learning Python or R, which are widely used in the field. Online resources, tutorials, and coding bootcamps can help you gain proficiency.
  • Gain knowledge in Data Manipulation and analysis: Familiarize yourself with data manipulation techniques using tools like SQL for Database querying and data extraction. Also, learn how to analyze and visualize data using libraries such as Pandas, NumPy, and Matplotlib.
  • Enroll in Data Science Courses or Bootcamps: Participating in structured data science programs specifically designed for non-technical backgrounds can provide you with a comprehensive understanding of the field. Look for programs that cover topics such as machine learning, data visualization, and predictive modeling.
  • Work on real-world projects: Build a portfolio of data science projects to demonstrate your practical skills and problem-solving abilities. Start with small projects using publicly available datasets or participate in Kaggle competitions to gain hands-on experience.
  • Networking and collaboration: Engage with the data science community by attending meetups, conferences, and online forums. Collaborating with professionals in the field can provide valuable insights, mentorship, and potential job opportunities.
  • Consider an internship or apprenticeship: Internships or apprenticeships can be invaluable for gaining practical experience and bridging the gap between your non-technical background and a data science role. Look for opportunities to work on data-driven projects and apply your skills in a real-world setting.
  • Continuous learning and staying updated: Data science is a rapidly evolving field, so staying updated with the latest trends, techniques, and tools is crucial. Engage in continuous learning through online courses, reading industry blogs, and participating in online communities.

Remember that transitioning into data science for non-technical background may take time and persistence. Emphasize your strengths, highlight your analytical thinking abilities, and leverage your unique perspective in problem-solving. With dedication and a strong learning mindset, you can successfully pursue a career as a data scientist.

How to get into Data Science from Non-Technical Background

Data Science Courses for Non-IT Students:

There are several IT courses for non-IT background students that you may opt for therefore, being able to develop your skills to become an expert. Accordingly, following are the Data Science Course with placement programmes:

  •       Pickl.AI Data Science Job Guarantee Program
  •       Data Science for Everyone by Data Camp
  •       Online Data Science Courses offered by Harvard University
  •       Introduction to Data Analytics by IBM, Coursera
  •       Free Data Science and Data Analytics Courses by Udemy
  •       Introductory Data Science Courses by Dataquest
  •       Data Analysis with Python by FreeCodeCamp


The above blog gives you a clear understanding of how can a non-Science student become a Data Scientist by following some crucial steps. From joining your preferred choice of course to becoming an expert with hands-on experience, your non-technical background is not the prerequisite to become a Data Scientist. With Pickl.AI’s Data Science Job Guarantee Program, you will be able to develop your Technical Skills from scratch and become an industry expert. It offers you with 100% placement guaranteed along with a one month internship opportunity with certification. Hence, if you’re a student or working professional from non-technical background willing to transition to a career in Data Science, Pickl.AI’s Data Science course with placement is the best option for you.


Although Data Science requires you to have a strong background in Mathematics and Computer Science, you can also pursue it if you’re from a non-technical background. With Data Science job roles rising in the market, even with a non-technical background, you can develop skills and knowledge to become an expert in Data Science.

As a Data Scientist, you need a strong background in Mathematics and Computer Science. You may not be from a technical background but with the help of different online certification courses, you can develop the skills you need to become a Data Scientist.

The most important subject for Data Scientist includes probability and Statistics which are mathematical capabilities you need to be proficient in Data Science.

Yes, you can become a Data Scientist with no experience while developing your skills and capabilities in Data Science. You need to develop your technical and non-technical skills to become a Data Scientist and solve business problems.

Yes, a non-programmer can learn Data Science by developing its programming skills and learning Python, R or SQL to become a Data Scientist.


  • Asmita Kar

    Written by:

    I am a Senior Content Writer working with Pickl.AI. I am a passionate writer, an ardent learner and a dedicated individual. With around 3years of experience in writing, I have developed the knack of using words with a creative flow. Writing motivates me to conduct research and inspires me to intertwine words that are able to lure my audience in reading my work. My biggest motivation in life is my mother who constantly pushes me to do better in life. Apart from writing, Indian Mythology is my area of passion about which I am constantly on the path of learning more.