Data Analytics with Python & AI

About this course

Disclaimer: This course contains the use of artificial intelligence(AI).Most data courses teach you Python syntax. This course teaches you how to think like a data analyst, work like a professional, and get hired like one. you will go from writing your first line of Python to deploying a complete data analytics project — with machine learning, AI-powered insights, interactive dashboards, and a GitHub portfolio that proves you can do the work.This is not a theory course. Every lecture has real data, real code, and real business decisions behind it.WHY THIS BOOTCAMP IS DIFFERENTEvery other Python for data course stops at the technical skills. This one goes further. You will learn how to use AI tools like the Anthropic API to analyze data 5x faster, how to communicate insights to executives using the SCQA framework, and how to position yourself for U.S. data analyst roles as an international professional navigating OPT, STEM OPT, and H-1B pathways.The skills in this course are not academic. They are the exact skills hiring managers test in data analyst interviews at U.S. companies right now.WHAT YOU WILL BUILDBy the end of this bootcamp you will have completed a full end-to-end analytics project . Your deliverables will include a clean, documented GitHub repository, a machine learning model that predicts high-value orders with over 80% accuracy, an interactive Plotly Dash dashboard your stakeholders can actually use, an AI-generated executive summary built with the Anthropic API, and an automated Python report that runs and emails itself on a schedule.That portfolio project is your most powerful job application tool. More credible than a certificate. More specific than a resume bullet.WHAT IS COVERED — DAY BY DAYFirst day covers Python foundations built specifically for data work. You will set up your environment, learn the only Python you actually need, and read your first real-world da

Course objectives

• to build a comprehensive analytics project
• to gain practical experience with real data and coding
• to prepare for data analyst roles in the U.S.