Data Scientist Scope

Because more and more sectors are depending on data-driven decision-making the field of data Science in India is predicted to expand dramatically over the next five years. The need for qualified data scientists is expected to increase by 2028 driven by industries including finance, e-commerce, IT and healthcare.Opportunities for Employment: India is set to emerge as a major centre for analytics worldwide. Data scientists, machine learning engineers and artificial intelligence specialists will continue to be in great demand.Pay Trends: Experienced professionals make up to the 25 LPA while entry-level workers make between 8 and 12 LPAIndustry Adoption: New fields like fintech driverless cars and the healthcare analytics will expand prospects.Maintaining relevance in this ever-evolving industry will need ongoing skill development in Python, R, AI and cloud technologies

Hello Gayatri, I will give you some guidance as per my knowledge on this subject. The field of data Science has been growing rapidly in recent years, and there is no sign of this trend slowing down. In fact, the scope of data Science is likely to expand even further in the years 2024-2025. Here are some of the key reasons to learn the Data Science. Growing demand for data-driven insights: As more companies and organizations realize the value of data-driven insights, the demand for data Science professionals is likely to increase. This is especially true in fields such as healthcare, finance, and marketing, where data can provide a competitive advantage. Increasing complexity of data: With the rise of big data and the Internet of Things (IoT), the amount and complexity of data that needs to be analyzed is growing rapidly. This creates a need for skilled data scientists who can extract insights from large and complex data Sets. Advancements in machine learning and artificial intelligence: The field of data Science is closely tied to machine learning and artificial intelligence (AI), which are rapidly advancing. These technologies enable data scientists to build more accurate models and make more precise predictions, which can have significant implications in fields such as healthcare and finance. Continued innovation in data Science tools and techniques: The tools and techniques used in data Science are constantly evolving, with new software and programming languages being developed all the time. This makes it an exciting and dynamic field to work in, and ensures that there will always be new opportunities for growth and innovation. Overall, the scope of data Science in the years 2024-2025 is likely to be very promising, with plenty of opportunities for skilled professionals to make a significant impact in their field. I wish you best of luck for the further studies ;). .

Dear Manish,
Well, you can learn in multiple ways, some people learn everything online while some join programs and courses to become a data scientist. I think one needs to cover a certain topics online while certain topics can only be learnt in classroom training module.
Python Basics, Intermediate and Advanced statistics, Probability and Linear Algebra, Linear Regression, Time Series and Cost Function, Types of Data & Exploratory Data Analysis, Collecting, extracting, querying, cleaning, and aggregating data for analysis, Data Sources, Cleaning and Wrangling, Working with APIs and Web Scraping.
These will help you learn the advanced topics of data Science faster and in depth. I would always recommend data Science aspirants to go for a programme which is classroom-based, instructor-led and heavily practice driven. You will come across a lot of institutions, courses, programs that will help you learn data Science. Some are way expensive while some are reasonable. But, one very important thing to keep in mind while you are enrolling for such courses is to know the worth of it in terms of knowledge and what at the end of the course you are developing within yourself. Remember: "80% practical & 20% theory".
Hope this helps.