Data Science

A promotional graphic for a "Zero to Hero in 26 Days" course focused on becoming a Data Scientist. The left side includes the CuriosityTech logo, a cloud icon, and text comparing Data Scientist vs Data Analyst vs ML Engineer. The right side shows a laptop with a holographic cloud image and a person typing.

Day 2 – Data Scientist vs Data Analyst vs ML Engineer Explained

When people hear the terms Data Scientist, Data Analyst, and Machine Learning Engineer, they often assume they mean the same role. But in reality, these are distinct professions—each critical in the journey from raw data to business insights and AI-driven products.

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Day 1 of a 26-day 'Zero to Hero' guide for becoming a Data Scientist in 2025. The title reads 'What is Data Science? A Beginner's Guide for 2025.

Day 1 – What is Data Science? A Beginner’s Guide for 2025

The world of technology in 2025 is driven by one phrase: data is the new oil. But unlike oil, data is infinite, renewable, and constantly evolving. Every click on a website, every purchase in an online store, every swipe on a smartphone generates data. Companies across healthcare, finance, e-commerce, education, and even agriculture are racing to harness this data for better decisions.

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Deep Learning: Unlocking the Power of Artificial Intelligence

Deep learning has emerged as one of the most transformative and exciting advancements in the field of artificial intelligence (AI). By mimicking the way the human brain processes information, deep learning allows machines to perform complex tasks such as image recognition, natural language understanding, and autonomous decision-making. In this blog, we’ll explore what deep learning

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Data Science: Unveiling the Power of Data for Modern Decision-Making

This blog explores the fundamentals of data science, its core components, and the impact it has on various industries. What is Data Science? Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It blends techniques from computer science, statistics, and domain

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