Basic 6–7 Hours12 Months Access

Business Sales Intelligence & Forecasting Platform

Build an end-to-end sales analytics platform with ML forecasting, interactive dashboards and real business insights.

Build an end-to-end sales analytics platform with ML forecasting, interactive dashboards and real business insights. Implement it step by step, deploy it, publish it on GitHub and prepare to explain it confidently in interviews.

Digital product · 12 months access · Non-refundable after purchase

app.streamlit / business-sales-intelli
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Complete Source Code

Deployment Guide

Resume Points

Interview Questions

What You'll Learn

Gain practical experience building a production-ready AI system, from architecture to deployment.

  • Core Sales Analytics concepts and when to apply them in real projects
  • Practical Data Analysis implementation techniques
  • Practical Machine Learning implementation techniques
  • Practical Streamlit implementation techniques
  • Structuring a clean, production-style Python project
  • Building an interactive Streamlit application
  • Deploying the application to the cloud
  • Explaining the project architecture confidently in interviews

Technologies Used

  • Python
  • Data Analysis
  • Machine Learning
  • Streamlit
  • Cloud Deployment

Project Architecture

Understand how the complete system components work together.

Data Sources

Sales CSV / ExcelTransactions
Product & RegionMaster data

Data Pipeline

CleaningPandas
Feature EngineeringSeasonality, lags

ML Layer

Forecasting ModelTrain & evaluate
Model MetricsMAE / RMSE

Application Layer

Streamlit DashboardKPIs, trends, forecasts

Deployment

Cloud AppStreamlit Cloud
A simplified view of the system you will build.

Project Demo

See the final application in action.

0:00 / 12:36

Preview of the final application you'll build.

    • 3 Lessons · ~45 Mins
    • 1. Project Overview15 min
    • 2. Real-World Use Cases8 min
    • 3. Final Architecture Walkthrough15 min