What is AI| Components of Data Science| Build Your First ML Model | No Code скачать в хорошем качестве

What is AI| Components of Data Science| Build Your First ML Model | No Code

What if I told you data science isn’t some futuristic tech-only magic — it’s something humans have been doing forever? 👵📊 In this beginner-friendly video, we’ll take a fun, relatable journey into how everyday decisions from the past mirror today’s machine learning models. From ancient farming to predicting monthly expenses, you’ll learn: ✅ What is AI ✅ How observation, pattern recognition, and decision-making form the roots of data science ✅ What linear regression actually means (without scary math!) ✅ How to model your monthly expenses — no code required ✅ The 3 pillars of Data Science: Domain Knowledge, Math & Statistics, and Computer Science ✅ Why grandma didn’t need Python to be a data scientist 😄 🎯 Perfect for: • Beginners curious about ML • Non-tech folks who want to understand AI • Anyone who thinks machine learning is “too complicated” ⸻ 👉 Bonus: We’ll also break down the equation y = b₀ + b₁x with a real-life example (like how parties affect your budget 😅), and show how simple math powers real machine learning. ⸻ 📌 Next Steps: Want to try this in Google Colab?    • Google Colab Tutorial | Code with Gen AI |...   How to write prompts? Follow below video:    • Prompt Engineering | Part 1: Prompts Struc...   Other relevant videos in ML series: EDA    • EDA - Part 1| Exploratory Data Analysis| N...      • EDA - Part 3| Exploratory Data Analysis | ...      • EDA - Part 2| Exploratory Data Analysis| B...      • EDA - Part 4 | Exploratory Data Analysis |...   Video: Statistical Concepts Explained (Mean, Std Dev):    • Mean, Median, Mode, Variance and Standard ...   Video: Normal Distribution and Skewness:    • Normal Distribution & Skewness Explained S...   Video: Evaluation Metrics for Regression Models Explained:    • MAE, RMSE, R², Adjusted R², MAPE — Evaluat...   Chapters: 0:10 Decisions were always data driven 2:54 Build your first ML Model - Monthly Forecasting 5:18 Use slope-intercept line to predict monthly expenses 7:46 Regression - Best Fit Line 8:46 The three pillars of Data Science - Math, Code and Domain Knowledge About Your Trainer: Manoj Tyagi holds a B.Tech degree from IIT Roorkee, is a CFA charterholder, and has completed a Postgraduate Program in AI/ML from the University of Texas at Austin. He conducts free online sessions every Sunday, specially designed for industry professionals looking to upskill in AI and Machine Learning. Phone# +6591574359 X: https://x.com/mkgraiitr LinkedIn:   / tyagimanojkumar   email id: mkgra.iitr@gmail.com 💬 Have questions or just vibing with the content? Drop your thoughts in the comments — I’d love to hear from you! 👍 Like, 💬 comment, and 🔔 subscribe if you’re ready to learn ML without losing your mind. #MachineLearning #NoCode #DataScience #AIForEveryone #MLForBeginners #AutoML #TechEducation #MLWithoutCoding #LearnMachineLearning #DataScienceMadeEasy #NoSetup #artificialintelligence #datascience #aiforbeginners #computerscience #maths #statistics #domain