🌍 Course Overview

Go from “I’ve worked with data before” to “I can deliver real data insights and build ML models” in just 6 weeks.

This course teaches real, practical data science using Python — the way it’s done today in the age of AI.
You’ll learn how to understand business problems, source real-world data, clean and analyze it, build simple machine learning models, and use AI tools like ChatGPT to speed up your workflow.

By the end of the course, you’ll complete a portfolio-ready data project that demonstrates your ability to turn messy data into meaningful insights.

🎯 Course Objectives

By the end of this course, you will:

• Understand the modern data science workflow from business question → insights

• Translate business requirements into measurable data tasks

• Work confidently with real-world datasets (CSV, Excel, JSON)

• Perform data cleaning, wrangling, and exploratory data analysis (EDA)

• Build and evaluate basic machine learning models using scikit-learn

• Create clear visualizations to tell compelling data stories

• Use AI tools to accelerate analysis, coding, and documentation

• Build a complete end-to-end data project for your portfolio

💡 Why This Course Is Different

✔ Practical, real-world data work — not academic theory
✔ Covers business alignment, not just Python
✔ Teaches how DS is practiced today using AI tools
✔ Hands-on every week — learn by doing
✔ Beginner-friendly, no math background required
✔ You finish with a real portfolio project
✔ Small live cohort with mentoring and feedback

You’ll learn exactly what modern data analysts and data scientists actually do — and how to use AI as a genuine productivity enhancer.

👥 Who This Course Is For

Perfect for:

• Beginners who want a clean, structured introduction to data science

• Professionals transitioning into data, tech, or AI roles

• Business and non-technical professionals who want to work with data

• Students preparing for analytics or data science careers

• Anyone who wants to understand how data + AI drive real decisions

🚀 Your 6-Week Journey

Week 1 — Understand the Business & Set Up Your Environment

Learn how real data science projects begin: with a business question.
Understand how data teams work, how to frame requirements, and set up Python, VSCode, and Jupyter.

Outcome:
“I understand the data science workflow and can set up a working environment.”

Week 2 — Load Real Data and Plan Your Analysis

Work with CSV/Excel data, explore structure, and turn business needs into measurable data questions.

Outcome:
“I can load, inspect, and break down a dataset into clear analysis questions.”

Week 3 — Clean, Transform, and Visualize Data

Fix missing data, convert types, and build professional visualizations using Pandas/Seaborn.

Outcome:
“I can clean data properly and create visuals that actually show insights.”

Week 4 — Build Your First Machine Learning Models

Learn what ML is, when to use it, and build your first classification/regression models using scikit-learn.

Outcome:
“I trained, evaluated, and interpreted my first machine learning model.”

Week 5 — AI-Assisted Data Science Workflows

Use ChatGPT/Gemini responsibly to accelerate coding, EDA, documentation, and reporting — like a modern data scientist.

Outcome:
“I can use AI tools to speed up my analysis while keeping accuracy and control.”

Week 6 — Capstone: Present Your Data Project

Deliver a professional data science project from start to finish:
business → data → EDA → visualizations → insights → (optional) ML → final report.

Outcome:
“I completed a full, end-to-end project that I can add to my portfolio.”

🛠 What You’ll Build

• A real data-cleaning and EDA notebook

• Multiple insight-driven visualizations

• Your first ML model (regression or classification)

• AI-assisted summaries, reports, and documentation

• A complete portfolio-ready capstone project

📈 Skills You’ll Gain

• Python for data analysis

• Data cleaning & manipulation with Pandas

• Exploratory data analysis (EDA)

• Data visualization (Matplotlib, Seaborn)

• Machine learning fundamentals

• Business problem framing

• AI-assisted data science workflows

• Project documentation & storytelling

💰 Investment & Guarantee

Course Investment:
Regular Price: $697
🦜 Early Bird Special — Save $200
Register by Dec 25: $497

Risk-Free Guarantee
“Build a portfolio-ready data project or your money back.”
If you complete the course and don’t feel confident using data science skills, we’ll refund you. No questions asked.

📅 Course Details

Schedule:
Next Cohort Starts: January 10, 2026
When: Saturdays, 10:00–11:30 AM EST
Duration: 6 weeks
Format: Live online via Zoom
Class Size: Maximum 20 students

What You Get:
✓ 6 live sessions with expert guidance
✓ Session recordings (lifetime access)
✓ Step-by-step exercises
✓ Downloadable notebooks and templates
✓ Private Discord community (24/7 support)
✓ Portfolio project review
✓ Career guidance for analytics roles
✓ AI workflow tips to boost real productivity

❓ Frequently Asked Questions

“Do I need prior experience?”
No. We start from the basics and build up progressively.

“What if I miss a session?”
All sessions are recorded, and community support is available anytime.

“Will I be able to work with real data?”
Yes — every week uses real-world datasets and hands-on exercises.

“Is this course useful if I’m already technical?”
Absolutely. You’ll learn the modern DS workflow and how to integrate AI effectively.

🌟 Ready to Level Up Your Data Career?

Join professionals who’ve transformed their skills and careers through hands-on, AI-enhanced data science.

Every day you delay is a day someone else learns to use data & AI better.

👉 [ENROLL NOW — LIMITED TO 20 SEATS]

👨‍🏫 Meet Your Instructor

Sudip Shrestha, PhD
Data Science & AI Lead
AI & Machine Learning Architect | Educator | Practitioner

Dr. Shrestha has built and deployed AI/ML solutions across federal agencies, startups, and enterprise environments.
His mission: make modern data science accessible, practical, and empowering — especially for beginners and career-switchers.

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