Best Learning Path to Becoming a Data Scientist

how to become a data scientist

Last Updated on July 6, 2024 by Team Experts

As per the US Bureau of Labor Statistics, the amount of Data Science jobs will increase by around 28% by the year 2026, which will approximately lead to the creation of over 11.5 million new jobs in this domain. It is safe to say that Data Science is one of the most sought-after career options opted by most IT professionals today and the demand for professionals will continue to rise. Enroll in one of the best Data Science Certification programs today and take the first step towards becoming a successful Data Scientist.

Before we read about the path that you can take to become a professional in this trending IT field, let us learn what Data Science is and who Data Scientists are.

What is Data Science?

Often professionals, including those in the field of IT, are confused about what exactly Data Science is and they mistake it for other similar technologies, like Business Analytics, Data Analytics, etc. Data Science is much different compared to these technologies. This interdisciplinary field of computer science consists of numerous models and algorithms that are responsible for visualizing, extracting, protecting, and identifying hidden trends and patterns in business data. This business data can be structured or unstructured.

This domain includes various techniques and methods, like statistics, AI, Machine Learning, data analysis, etc., that help to extract valuable information from raw business data.

Who is a Data Scientist?

Data Scientists are expert professionals in the field whose main job role in an organization is to extract and analyze large volumes of business data and find patterns that can be helpful for users and organizations. These professionals use a range of analytical tools and technologies for advanced analytics, predictive modeling, Machine Learning algorithms, etc. Further, they make use of a range of visualization tools that allow them to present the insights they have gathered via data collection and data mining. This, in turn, allows them to make well-informed business decisions that can help in business growth, offers new revenue opportunities, leads to customer-oriented decisions, and more.

Now, let’s understand how you can get into this demanding profession.

Steps to Become a Data Scientist

The internet is a place filled with information about Data Science and its various sectors and modules. However, this data is so vast that it can be confusing for beginners in this domain. Here is a laid-out path on Data Science for Beginners and experienced professionals that you can follow in order to become a Data Scientist.

Step 1: Gain Proficiency in Python and R Programming Languages

R programming language is significant for statistical computing as it allows Data Scientists to build data analysis and statistical software. Python, on the other hand, is a high-level language that is used across numerous applications and domains. Python is an easy language to learn which is why most professionals start off by learning it before getting into Data Science or any other IT field. There are various resources available online to learn both these languages. For Data Science, it is important that you become skilled in at least one of the two languages so that you can use them to build the required applications and analyze business data easily.

Step 2: Learn to Communicate with Databases

Data is the most crucial part of Data Science and it is the job of a Data Scientist to tell a story with the help of this data. A Data Scientist is responsible for analyzing and visualizing the data which is stored in a database. This is why it is important for these professionals to interact with the database, become capable of designing databases. For that, you must become an expert in SQL or Standard Query Language as it will allow you to communicate with these databases. Like Python and R, there are various resources available online and offline for you to learn this query language and become an expert in it.

Step 3: Expertise in Statistics and Mathematics

Mathematical and statistical concepts are the core modules that all Data Scientists need to have expert knowledge in. You should have basic knowledge in skills in statistics, probability, linear algebra, and other significant topics. Moreover, most of the Data Science tools that you will use for the purpose of working with business data. So, before learning Data Science, you should acquire statistical and mathematical skills.

Step 4: Familiarize Yourself with Version Control Concepts

Data Science professionals are expected to write various code files and explore datasets. The changes made in the code can be tracked using version control systems, like Git. Git is a popular version control system that allows professionals to keep a track of all the changes made in the source code during the process of software control. Further, it also allows team members to coordinate their work while developing the code and track the changes made by any individual in any particular code file.

Step 5: Knowledge of Basic and Advanced Level Data Science Concepts

To become a Data Scientist, you need to master all the significant modules, concepts, and tools in the field of Data Science, including R, Hadoop, Python, Spark, Deep Learning techniques, Machine Learning algorithms and concepts, SQL, etc. You also need to learn and work with various data visualization tools that will help you present the information you have gathered from the data to the other members of the organization.

Step 6: Gain Working Experience in Data Science

In order to land a high-paying job in the field of Data Science, it is vital for you to gain professional experience in the numerous Data Science tools and technologies to gain hands-on experience in the field. This will substantiate your learning and also act as a bonus in your resume, making you one step closer to your dream job. Moreover, it will help you to experience the various tools that you will be required to work with as a Data Scientist. This can be beneficial for your career and will keep you one step ahead of your competitors.

Step 7: Enroll in a Data Science Course

Sign up for one of the best training programs in Data Science so that you can acquire all the required skills to become a professional in this field. Further, several online courses, including the Data Science course at Intellipaat, offer industry-based assignments and projects that are directed towards enhancing your learning experience.

Step 8: Go Through Free Online Resources

There are several online resources available on Data Science for free, including blogs, tutorials, YouTube videos, etc. These resources are extremely useful, especially for beginners who wish to get a basic idea of the technology before moving ahead with online or offline Data Science courses. You can also prepare for job interviews via blogs on Data Science interview questions, consisting of the latest and most frequently asked interview questions by recruiters and major organizations.


Here, we discussed in detail the best path that you can opt for to learn and become a Data Scientist. To learn all the skills and become an expert in them, you must sign up for a course in this field. In this blog on the best learning path to become a Data Scientist, you have also read in brief and got the basic idea of what Data Science means and what professionals in this domain do. So, if you wish to become a Data Scientist, sign up for a training program without wasting any time and take the first step towards a successful Data Science career.

Also read about: Best Programming Languages for Data Science


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Anil is an enthusiastic, self-motivated, reliable person who is a Technology evangelist. He's always been fascinated at work especially at innovation that causes benefit to the students, working professionals or the companies. Being unique and thinking Innovative is what he loves the most, supporting his thoughts he will be ahead for any change valuing social responsibility with a reprising innovation. His interest in various fields and the urge to explore, led him to find places to put himself to work and design things than just learning. Follow him on LinkedIn

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