Prompt EngineeringSimple Project – AI Sales Analysis Project скачать в хорошем качестве

Prompt EngineeringSimple Project – AI Sales Analysis Project

Prompt Engineering Simple Project – AI Sales Analysis Project You only need: • Python (Jupyter Notebook) • SQL (optional) • ChatGPT ________________________________________ 🪜 STEP 1 – Download Dataset Go to Kaggle and download Superstore Sales Dataset. Search: “Superstore Sales Dataset Kaggle” Download CSV file. Put it in your project folder. ________________________________________ 🪜 STEP 2 – Open Jupyter Notebook Create new notebook: AI_Sales_Project.ipynb ________________________________________ 🪜 STEP 3 – Load Data (Python) Write this code: import pandas as pd df = pd.read_csv("superstore.csv") df.head() Now you see your data ✅ ________________________________________ 🪜 STEP 4 – Clean Data (Very Simple) Paste this: Remove duplicates df = df.drop_duplicates() Check missing values print(df.isnull().sum()) Convert date column df['Order Date'] = pd.to_datetime(df['Order Date']) df.describe() Now data is clean ✅ ________________________________________ 🪜 STEP 5 – Basic Analysis Add this: Total Sales total_sales = df['Sales'].sum() print("Total Sales:", total_sales) Sales by Region region_sales = df.groupby('Region')['Sales'].sum() print(region_sales) Monthly Sales df['Month'] = df['Order Date'].dt.to_period('M') monthly_sales = df.groupby('Month')['Sales'].sum() print(monthly_sales) Now you did real analysis 👏 ________________________________________ 🪜 STEP 6 – Use AI for Insights Copy your monthly_sales result. Go to ChatGPT and write: You are a business analyst. Here is monthly sales data: [paste result] Give: 5 insights 3 risks 3 recommendations Executive summary in 100 words Now AI helps you like company consultant 💼 ________________________________________ 🪜 STEP 7 – Dashboard Suggestion Ask ChatGPT: Suggest Power BI dashboard layout for sales analysis. Include: KPI cards Charts Filters Now build same dashboard in Power BI. ________________________________________ 🪜 STEP 8 – Save Project Save notebook. Upload to GitHub. ________________________________________ 🏆 What You Just Built ✔ Data cleaning ✔ Data analysis ✔ AI insight generation ✔ Dashboard planning ✔ Real business workflow This is real project. Prompt Engineering Simple Project – AI Sales Analysis Project You only need: • Python (Jupyter Notebook) • SQL (optional) • ChatGPT ________________________________________ 🪜 STEP 1 – Download Dataset Go to Kaggle and download Superstore Sales Dataset. Search: “Superstore Sales Dataset Kaggle” Download CSV file. Put it in your project folder. ________________________________________ 🪜 STEP 2 – Open Jupyter Notebook Create new notebook: AI_Sales_Project.ipynb ________________________________________ 🪜 STEP 3 – Load Data (Python) Write this code: import pandas as pd df = pd.read_csv("superstore.csv") df.head() Now you see your data ✅ ________________________________________ 🪜 STEP 4 – Clean Data (Very Simple) Paste this: Remove duplicates df = df.drop_duplicates() Check missing values print(df.isnull().sum()) Convert date column df['Order Date'] = pd.to_datetime(df['Order Date']) df.describe() Now data is clean ✅ ________________________________________ 🪜 STEP 5 – Basic Analysis Add this: Total Sales total_sales = df['Sales'].sum() print("Total Sales:", total_sales) Sales by Region region_sales = df.groupby('Region')['Sales'].sum() print(region_sales) Monthly Sales df['Month'] = df['Order Date'].dt.to_period('M') monthly_sales = df.groupby('Month')['Sales'].sum() print(monthly_sales) Now you did real analysis 👏 ________________________________________ 🪜 STEP 6 – Use AI for Insights Copy your monthly_sales result. Go to ChatGPT and write: You are a business analyst. Here is monthly sales data: [paste result] Give: 5 insights 3 risks 3 recommendations Executive summary in 100 words Now AI helps you like company consultant 💼 ________________________________________ 🪜 STEP 7 – Dashboard Suggestion Ask ChatGPT: Suggest Power BI dashboard layout for sales analysis. Include: KPI cards Charts Filters Now build same dashboard in Power BI. ________________________________________ 🪜 STEP 8 – Save Project Save notebook. Upload to GitHub. ________________________________________ 🏆 What You Just Built ✔ Data cleaning ✔ Data analysis ✔ AI insight generation ✔ Dashboard planning ✔ Real business workflow This is real project. contact paid course 9168531394