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"What Is Data Science? Explained in Just 5 Minutes!" In this video, we break down the data science process in just a few minutes, making it easy for beginners to understand. You’ll explore the complete data science life cycle from identifying business problems and acquiring data to preparation, exploratory analysis, modeling, and deployment.

This is a data science tutorial for beginners designed to give you a simple explanation of data science and how it is applied in real companies. You’ll also learn what a data scientist does, the importance of presenting insights, and how data science applications are transforming industries worldwide. Whether you’re completely new or just want a quick introduction to data science, this video gives you the clarity you need to get started.

Below are the topics covered in this video 'What Is Data Science?':
00:00:00 - Introduction to What is Data Science
00:00:18 - Step 1: Understanding Business Problem
00:00:38 - Step 2: Data Science Acquisition
00:01:10 - Step 3: Data Preparation
00:01:46 - Step 4: Exploratory Data Analysis
00:02:31 - Step 5: Modeling
00:03:10 - Step 6: Presenting Insights to Stakeholders
00:03:31 - Step 7: Model Deployment
00:04:01 - How Data Science is Transforming the Industry

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➡️ About Data Science Course:
This online Data Science course, in collaboration with iHUB, IIT Roorkee & Microsoft, will help you to elevate your Data Science career. In this course, you will master skills like Python, SQL, Statistics, Machine Learning, AI, Power BI & Generative AI, along with real-time industry-oriented projects.

➡️ Key Features:
✅ 50+ Live interactive sessions across 7 months
✅ 218 Hrs Self-paced Videos
✅ 50+ Industry relevant Projects & Quizzes
✅ Live Classes from IIT Faculty & Industry Experts
✅ Certification from iHub IIT Roorkee & Microsoft
✅ 2 Days Campus Immersion at iHub IIT Roorkee

➡️ What’s Covered in This Program?
✅ Linux and Python Fundamentals
✅ Data Wrangling with SQL
✅ Python with Data Science
✅ Linear Algebra and Advanced Statistics
✅ Machine Learning and Prediction Algorithms
✅ Supervised and Unsupervised Learning in ML
✅ Deep Learning with TensorFlow
✅ Generative AI & Prompt Engineering
✅ Deploying Machine Learning Models on Cloud
✅ Data Visualization Tool Power BI

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