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Do we need prior coding experience for learning data science?

No, you don't necessarily need prior coding experience to learn about data science, but it might come in handy. Most introductory data science classes are geared towards people with no or little programming experience. These classes tend to introduce programming concepts slowly, employing beginner-friendly programming languages such as Python or R. You'll be able to create simple scripts, work with data, and use common libraries used for data analysis and visualization.

The most important thing is that you be willing to learn and practice regularly. With so many tutorials, online courses, and interactive tools available, even a non-technical person can learn coding by the way. But once you go on, coding becomes a part of your toolkit for data cleaning, machine learning model development, and workflow automation.

In short, previous coding experience is not necessary to start learning data science but mastering coding skills is one of the key elements involved in becoming a professional data scientist.

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Why is data science used?

Data science is employed to extract meaningful insights from big data, allowing companies to make informed decisions. It combines statistics, programming, and domain knowledge to sift through intricate data sets and identify latent patterns, trends, and relationships. Companies use data science for customer segmentation, sales forecasting, fraud detection, and product recommendation. In medicine, it is used to predict diseases and personalize care. In finance, it is used to aid in risk analysis and algorithmic trading. Governments use it in policy-making and improving public services. With data science, companies can improve efficiency, reduce costs, and gain a competitive advantage. It also helps to develop AI systems, such as recommendation systems and chatbots. In the digital economy, data science helps make effective, accurate, and timely decisions across all areas of business.
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