Data Analytics with Python & AI

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 dataset. Day 2 covers data cleaning and wrangling with pandas. You will handle nulls, fix data types, remove duplicates, merge DataFrames, and build an analysis-ready dataset from scratch.

Day 3 covers exploratory data analysis. You will apply descriptive statistics correctly, build professional visualizations with Matplotlib and Seaborn, and generate 10 business insights from a real e-commerce dataset without touching a single machine learning model. Day 4 covers AI-assisted analysis.

You will make your first API call to a large language model, build a personal analyst assistant in Python, and master prompt engineering techniques specifically designed for data tasks. Day 5 covers machine learning fundamentals. You will build regression and classification models with scikit-learn, interpret every output in plain English, and evaluate your models correctly using cross-validation, confusion matrices, and F1 scores.

Day 6 covers dashboards and data storytelling. You will build interactive dashboards with Plotly and Dash, structure analyst presentations using the SCQA framework, and automate a complete reporting pipeline that generates and emails a PDF report on a schedule. Last Day covers your capstone project and career positioning.

You will complete a full end-to-end analytics project, publish it on GitHub with a recruiter-ready README, and build a 30-day job search action plan designed specifically for international professionals in the U. S. market.

WHO THIS COURSE IS FORThis course is built for international students and professionals on F-1, OPT, or STEM OPT who want to transition into data roles in the U. S. It is also for working professionals in non-technical fields who want to upskill into analytics without a computer science background, and for early-career analysts who know the basics but have never built a complete portfolio project or integrated AI into their workflow.

You do not need a mathematics degree. You do not need prior programming experience. You need a laptop, a willingness to write code alongside the lectures, and a goal to land a data role.

REQUIREMENTSNo prior Python experience is required. A computer with internet access and at least 8GB of RAM is sufficient. All software used in this course is free and open source.

API usage in the AI modules requires a free account — setup is covered in the lecture. A NOTE ON CAREER OUTCOMESData Analyst, Business Intelligence Analyst, Analytics Engineer, and Data Scientist roles are among the most consistent H-1B sponsoring positions in the U. S.

market. All qualify for STEM OPT extension under the relevant CIP codes. This course does not just build your technical skills — it builds the portfolio evidence that makes your application stand out to employers who sponsor visas.

Every skill in this bootcamp was chosen because it appears in job descriptions, gets tested in interviews, and transfers directly to your first week on the job. Enroll now. Your portfolio project starts in the first lecture.