How To Start A Career In Data Science With No Coding Background?

By Author: Reshma
Total Articles: 3
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A new career in data science is exciting but will be a challenge for you if you haven’t had any experience with coding. Many students are asking this question: “Can someone without the knowledge of programming become a data scientist?”
Data science is one of the most in-demand professions today, and companies are hiring students from all different backgrounds, so it does not matter what your major was; whether you are a commerce student, an arts student, a management student, or a life sciences student, or even a non-technical student, you can build a successful career in data science.

The most important thing to remember is that you need to know where to begin and that you can proceed step by step.

So, let us simplify this a little bit:

1. Understand What Data Science Means

Before you worry about coding or tools, you should understand what data science means. Data science is about:

Collecting Data

Cleaning and Organizing Data

Finding Insights

Helping Business Decisions

You do not need a technical background to understand this definition of data science. ...
... Data science can also be understood as problem-solving using data.

Many Students believe Data Science means Machine Learning and Coding, but understanding Business Problems and Logic is just as important as understanding the technology or programming concepts.

2. Understanding data basics first; No coding required.
When you are new to the world of Data Science, make sure you understand the basics first such as;
What is Data?
What is Data Analysis?
What is Machine Learning?
Where does Data Science take place?
What tools do Data Scientists use?
You can gain a good foundation of Data Science through some free courses and beginner YouTube videos, that way you will have some knowledge before moving on to programming or having to learn it.
Many institutes that offer a Data Science course, also generally have an introduction into Data Science courses from zero.
When searching for a technology course like AWS in Coimbatore, many students will be searching for a course in Data Science that starts from scratch.

3. Learning one programming language to begin.
You only need to learn Python
You don't need to be an expert coder. You simply need to understand;
Variables
Loops
Data types
Functions
Python is a simple programming language that is suitable for beginners; about 90% of Data Scientists use Python. There are now many advanced software technologies that assist in making coding less complex, so do not fear coding. The most important thing is to remain consistent with your learning, instead of becoming an expert.

4. You only need to understand basic maths for Data Science
Most students think that they have to be an expert mathematician to get into Data Science.
The only mathematical knowledge that is necessary to get started with your Data Science studies, are as follows:
Basic statistics
Basic probability
Graphs
Mean, Median, Mode
Basic linear algebra
You don't need to become a mathematician! You only need to have concepts of maths in order to do Data Science.

5. Familiarize Yourself With Data Tools
Once you understand the fundamentals of data science, it's time to familiarize yourself with the types of data tools that companies use every day, including:
- Python Libraries: Pandas, NumPy, Matplotlib
- SQL (to Query Data)
- Excel (an essential tool for Beginners)
- Power BI or Tableau (to Create Dashboards)

All of these data tools will allow you to work with Data without requiring extensive coding knowledge or experience. There are also many additional avenues for improving your technical skill set or Software training (e.g. AWS course in Coimbatore). Many institutes providing training in India will provide you with an option for learning Data Science as part of the curriculum.

6. Start Working on Mini Projects (Even Small Projects are Important)
Completing mini-projects is a great way to build confidence when starting out as an analyst. To start, it is helpful to attempt these beginner projects:
- Predicting the Price of a House
- Analyzing the Sales Data of a Company
- Segmenting Customer Bases
- Predicting Weather Conditions
- Analyzing Student Performance

You can also find sample datasets on Kaggle to practice. Again, the goal of building confidence through mini-projects is not perfection but to provide you with practical, hands-on experience in working with Data.

7. Develop a Simple Portfolio
To demonstrate to recruiters that you can apply the skills you have gained in Data Science, it is essential to create a Simple Portfolio that includes the following:
- 3 to 5 beginner-level projects
- Your GitHub Profile
- Your LinkedIn Profile
- Basic Resume listing the tools you have experience using

The use of a Simple Portfolio allows recruiters to see the skills you have acquired and the experience you have gained in Data Science.

8. Know How the Sector Functions
If you know the terms in your industry, you are ready for a job in that sector. Here are examples of terminology you will find in the Data Engineering field:

* What does Supervised Learning mean?
* What does Model mean?
* What does Data Cleaning mean?
* What does Feature Engineering mean?
* What does Model Accuracy mean?

All the terms you read about build your confidence to answer questions in job interviews.

Technical Training Institutes, which provide users with access to real-world examples of data engineering projects (e.g., enrolling in an AWS course in Coimbatore) allow students to become acquainted with what it means to be a successful Data Engineer and provide the opportunity for them to learn about what employers expect.

9. Look at Internships and Real-World Experience
Internships can help students succeed even if they are short-term:

* Work on Real Datasets
* Teamwork
* Business Needs
* Communication
* Confidence

If the candidate can show a strong willingness to continue to learn and has gained practical experience, many businesses will hire fresh candidates.

10. Keep at It & Keep Learning
Data Science/A Data Engineer is a journey — not something you will accomplish overnight. If you become acquainted with the process and use a structured method, you will be able to enter this new Data Engineer field even if you have no experience coding.
Xplore IT Corp provides an accessible way for anyone interested in Data Science to acquire the skills to become employed in Data Science. Our instructors will assist you through each step: starting with introductory content through practical examples so you feel comfortable completing the course, even if you do not have any technical experience.

Frequently Asked Questions - Related to This Article

1. Is it possible to be successful in Data Science without coding skills?
Yes! You can start learning Data Science by focusing on concepts before moving into programming language.

2. How long will it take to be proficient in Data Science if I have never taken a class on Data Science?
Typically, beginners that are committed to ongoing learning can obtain an entry-level job in Data Science in four to six months.

3. Is there an extensive mathematics background required to obtain a Data Scientist position?
No, the majority of work done as a Data Scientist requires only basic statistics and logical reasoning.
4. Are individuals with arts or commerce degrees able to enter into Data Science fields?
Yes! Many Data Scientists were not trained in the field of technology prior to pursuing Data Science.

5. What are some recommended tools for novice Data Scientists?
Python, Excel, SQL, and Power BI are common tools to use for beginning Data Science practitioners.
https://www.xploreitcorp.com/data-science-course-in-coimbatore/