The Complete Guide To Becoming A Data Scientist In India

Data science has become one of the most in-demand and sought after professions in the world. With the advancement of technology, businesses are recognizing the potential in harnessing data to gain new insights, create better products and outmaneuver competition. In India, employers across industries are increasingly hiring data scientists and adopting data-driven strategies to drive growth.

What Is A Data Scientist?

A data scientist is an individual who is responsible for collecting, processing, and interpreting various types of data. Through their expertise in the area of machine learning, mathematic techniques and other AI-related areas, they can identify problems, analyze data, and develop solutions to address the difficulties that are faced by the industry. They are well-rounded professionals with exceptional analytical and language processing skills. They possess the knowledge to study data and provide insights that can be used in data-driven decision making.

Where Can I Learn Data Science?

Among the available options, there are two popular methods for learning data science: online courses and certification programs. Taking online courses is your surest and quickest way to specialize in data science. There are plenty of free and paid resources available online to help you become a data scientist. Sites like Udemy, Coursera, EdX, and Udacity offer plenty of courses on analytics, big data, artificial intelligence, machine learning, and database management fundamentals. You can even enroll in a university or college to learn data science. Several universities, such as Indian Institute of Technology, offer online degrees in data science.

Steps Required To Become A Data Scientist In India

Although becoming a data scientist can be a daunting endeavor, the rewards can be great. It takes a lot of hard work and preparation. However, if you want to acquire the skills and knowledge needed to become a data scientist, here are the five fundamental areas that must be focused on.

1. Get Familiar With The Basics

It’s essential to get familiar with the basics of data science before proceeding to the next step. A basic knowledge about the topics such as Python, R programming, Machine Learning, Statistics, etc. are essential for a successful career in data science. It is also important to build your foundational skills by learning how to wrangle, clean, and prepare data sets, as well as having a basic understanding of the various visualization techniques.

2. Enhance Your Skillset

It is important to focus on areas such as data engineering, machine learning, deep learning, image/video processing and natural language processing in order to become a successful data scientist. Having a strong foundation in math and science will also help to solidify your understanding in the topics above. Additionally, familiarizing yourself with data analysis, data visualization, and software engineering tools like Tableau, Pandas and Scikit-Learn can be beneficial.

3. Become Certified

After having a good handle of the basics of data science, it is important to enhance your resume through certifications or professional membership. There are a number of organizations who offer certifications for aspiring data scientists. For example, Coursera offers a number of data science specializations such as Machine Learning, Applied Data Science, Data Analysis and Visualization. Additionally, organizations like the Association of Data Analytics Professionals also offer certifications in analytics and data management.

4. Acquire Relevant Experience

In order to build a successful career in data science, it is important to have experience, which can be acquired through internships, hackathons, open-source projects, or even creating your own projects. Participating in hackathons and internships will not only help you acquire relevant experience but also boost your portfolio, which can help to get an edge over other job applicants. Additionally, taking part in open source projects will allow you to network with experienced data scientists, which can also be beneficial in the future.

5. Stay Up To Date With The Trends

As data science is constantly evolving, it’s important to keep up to date with the most recent trends and tools. Reading books and blogs about data science, attending webinars, seminars and conferences, as well as joining online data science communities are a great way to keep up to date with the latest developments. Additionally, networking with experienced professionals can also help to gain insights into the industry and discover career opportunities.

Conclusion

Data science is an in-demand and competitive field, where the demand for qualified professionals is high compared to the available resources. Becoming a data scientist is no easy feat, but with a strong foundation, relevant certifications and experience, staying up to date with the trends, and networking with like-minded professionals, a career in data science is possible.