Is Data Science Hard? A Non-IT Student’s Guide to Decoding Complexity

In the advancing world of technology, people are more into facts and accurate ratios of probability. Therefore, data scientists are working on different platforms to find and research those facts and probabilities through different methodologies. For that exact reason, the need for technological people increasing in the United States market, and people who are not from the science stream wants to join the market as data scientist but do not know what are the requirements or what they should do in the end make the mind thinking data science hard. So in this article, we will be mentioning those points that you will need to become a data scientist as a non-technical person.

Is Data Science Hard?

Common Misconceptions- Dispelling the Myth of Difficulty 

Being a data scientist is not hard anybody can be one with some appropriate knowledge and skills. Most people all around the world don’t know what data scientists do or what kind of study or skills they need to be one. In the end, the question stays at Is data science hard? So, to break the ice at first try out contacting, and connecting knowledgeable people and if you are unable to do that try doing research on it as that is what data scientists would do.

Emphasizing the Importance of Mindset

Whenever a person aims to be a data scientist and questions is data science easy to learn he starts to think rationally about every work he is assigned. Generally, a data scientist’s job is to collect data from different sources and understand the amount of error that reports have cleaning in the process and arranging it for a better understanding and presentation. If people see the process of their daily job it’s a common task which they do in their daily office lives. 

Roadmap for Non-IT Students

Building a Foundation 

As a non-IT student, your thoughts on being a data scientist can be an interesting idea but it will be out of your reach. We assure you that it’s not like that anybody can be a data scientist until he knows how to achieve it. For the foundation part gather information about what kind of data scientist you want to be as there are many categories of data scientists in the market who work for different organisations and clean different data for them.

Also, reading different research papers will help you to understand the methods they use when they are doing their data scientist job. Additionally, the person doesn’t need to be an expert in most subjects but should be able to do basic maths instantly so practising will be a good decision. Also, the topic probability and set are the most important ones in the field. Plus the subjects in which field you aim to be a data scientist.  

Understanding Data 

Understanding the data is a very important part of being a data scientist. In our daily lives whatever we hear or read is data. However, the thing which is not known by many is that data is divided into two categories one is primary and the other is secondary. The difference between these two types is primary data is collected from live audiences and secondary data is basically a report or information present on the internet or books not directly taken from the audiences. In the research field people do research with both kinds of data and call those research qualitative and quantitative research work.
If both types of data are compared on the basis of their correctness it can be done as it purely depends on that data scientist how he has done it. If the result of the research is not satisfying that is understandable but after doing the research and not getting an answer means there is a mistake. Whenever you see your research doesn’t get a result don’t be fade up change the methods and try again because that what a data scientist does.  

In between those research, you must be having doubts about what method we are mentioning again and again. As Data scientists, you need to learn about those methods too because without those methods clean those two types of data and take out exactly that part which information they need in their work.   

How to Get into Data Science

Choosing the Right Educational Path 

The right educational path to choose for being a data scientist is a bachelor’s degree in data science or any engineering degree which tries to make each student proficient in data use. However many students during their school graduation time are not aware of the fact that doing a bachelor’s degree in data science can help them become data scientists. They think that for this course need to have a science stream in their major. For those who think this is not true actually anybody from any major can do this bachelor’s degree in data science until he has maths or computer application in his background. One more thing each college has its own eligibility criteria so it depends on them that they are finding a student with an additional subject but having maths will work in most cases.  

For those who think that they are late to get into the field of data science and is data science hard. It is not like that, you can join the field by doing additional courses and internships it will be hard but not impossible. Just search for courses online to gain practical skills and knowledge on the subject and try working for organisations in the same field as an intern or part-time for a time to gain experience. 

Gaining Practical Experience 

Whenever you are starting a new field you are not experienced in or do not have the educational background in that field try to gain relevant knowledge in that field and go for courses and workshops provided by people online for free before investing in a course or training institute. That is because it will increase your knowledge in the field somewhat from not having to have is better. 

Networking and Community Engagement 

As it is mentioned to explore new things you have to expose yourself to new knowledge and people who are experts in that field. It is common everywhere and in data science it is also the same. Finding people individually can be a difficult task so go for communities their you will find the best teacher learner and creator who can teach you new things about the subject. However, just don’t listen to them engage in conversation introduce yourself and as long as you are honest you are good to go for the field. 

Is Data Science Easy to Learn?  

This is a common question many have before starting the exploration of the data science field to become a professional data scientist. The answer is yes until you are interested and hard working to achieve that interest of yours. There is not much difference in the learning part as others learn from courses, books, and material you can do it. Some also start working and in the process learn that also possible just the interest and hard work must be there. Remember data science is a huge field and full of opportunities while learning you will automatically develop all the necessary requirements and what you want to do in that field. So be patient and start at your own pace no need to hurry.

Overcoming Challenges

Common Challenges Faced by Non-IT Students

If we talk about the challenge a person can face who doesn’t have the educational background or the skills required to be a data scientist. There are a lot of points and a list but those are minor challenges everybody faces at the start and in some cases, they are not aware of some point they are already good at after realising it feels great that they have learned it. However, a non-IT person who has never touched the basis of computer science will face trouble with it as he needs to learn at least the computer applications to be able to work on it.

Then the person who has not done maths in a while will have to again start practising it not all the mathematical part but the set and probability part mostly. Also, need to be able to work on the latest tools which organisations use for their working environment. In the end, the basic challenges remain like dedication, concentration, and maintaining your interest all and we hope you will able to work on those and able to achieve the knowledge and skills you trying to gain.   

Strategies for Success

This whole document is the strategy because each point and heading holds valuable knowledge for you to learn and apply to be successful in the field of data science. However in a short manner to be successful be curious about the topics, search for new things in the field, communicate with people to share your insights and likings to understand the domain more and do your research impactfully so it’s sound in the successful corner.


From the overall document, a Non-It person will understand the basics of data science and techniques. Plus he will be able to understand the pros and cons he will face during the beginning of the struggle. In the end, how he should achieve his goal are mentioned and from those point, it is clear to everybody that it is not like a non-IT person cannot be a data scientist if he wants to be one.