How I Used Google Gemini to Automate My $90K Data Science Job скачать в хорошем качестве

How I Used Google Gemini to Automate My $90K Data Science Job

🚀 Gumroad Link to Assets in the Video: https://bit.ly/420zs8b 🤖 Join My Community Exclusive Content ➡ https://bit.ly/3ZMWJIb 📅 Book a Meeting with Our Team: https://bit.ly/3Ml5AKW 🌐 Visit Our Website: https://bit.ly/4cD9jhG What if working with datasets was as easy as dropping a file and typing a prompt? In this 23-minute deep dive, I break down a brand new Gemini feature that automates everything from data cleaning and visualization to forecasting and churn prediction—without needing to write much code. You'll watch as I upload datasets, issue simple prompts, and watch Gemini generate full-scale data analyses worthy of a junior data scientist. I test this across multiple scenarios using three hypothetical datasets—one for automation optimization, one for forecasting performance, and another for churn prediction—each revealing just how far you can go with AI in just a few clicks. If you've ever wanted a plug-and-play data analyst, this video shows you exactly what's possible in 2025. ⏳ TIMESTAMPS: 00:00 – Intro: Gemini’s mind-blowing new feature 00:41 – What is Colab and why it matters here 01:36 – Gemini in action: Drag-and-drop to analysis 02:55 – Uploading and exploring the automation dataset 04:16 – Prompting Gemini for deep trend analysis 05:01 – Full breakdown of Gemini’s auto-analysis steps 06:27 – Real-time error correction and insight generation 07:05 – Visualizations: Time-consuming tasks & pie chart critique 08:15 – Optimization scoring: Ranking tasks by automation potential 09:30 – Summary insights & “mini-consultant” recommendations 10:52 – Forecasting demo: Creating hands-off trend analysis 12:20 – Visualizing leads, conversions, and revenue over time 13:14 – Detecting seasonality, trends, and correlations 14:04 – Preparing data for forecasting models 15:00 – Forecast results and interpretation 15:42 – Richer EDA: Multi-feature analysis with new dataset 16:35 – Automated plots for age, gender, income, occupation 17:10 – Correlation heatmaps and deeper insights 18:10 – Making visual dashboards with Plotly 18:56 – Final experiment: Predictive modeling with churn dataset 19:50 – Feature engineering, model building & evaluation 20:55 – Feature importance and actionable business insights 21:56 – Using AI instead of hiring junior analysts 22:40 – What's next: Dashboards from prompts and future potential 23:10 – Access notebooks, datasets, and join the community #Gemini #GoogleGemini #AI #AIDataAnalysis #ForecastingWithAI #ChurnPrediction #AutoML #ExploratoryDataAnalysis #DataScience2025 #MachineLearning #InteractiveDashboards #NoCodeAI #GoogleColab #Plotly #AutomationAnalysis #BusinessAnalytics