What you'll learn:
- Develop the skills to explore, visualize, and understand raw data
- Learn how to select the most impactful features
- Handle missing data
- Explore advanced methods like dimensionality reduction
1. Data Types Demystified
Understand Nominal, Ordinal, Interval, and Ratio features.
Learn how to visualize and interpret feature types with ease.
2. Speed Up EDA with Manus (AI Tool)
Use Manus, an AI-powered assistant, to accelerate your Exploratory Data Analysis.
Automatically generate charts, summary statistics, and insights — fast.
Let AI help you find patterns and outliers without coding everything manually.
3. Handling Missing Data Like a Pro
What missing values are and why they matter.
Practical strategies to fill in numerical and categorical gaps.
4. Smart Feature Selection
Use ANOVA F-Test, Chi-Square, and RFE to choose only the most useful features.
Build leaner, faster, and smarter models.
5. Feature Engineering with ChatGPT
Use ChatGPT prompts to brainstorm and build new features automatically.
Accelerate your workflow with AI-powered feature creation — no coding stress!
6. Dimensionality Reduction with PCA
Learn what PCA is and when to use it.
Reduce complexity while preserving the most important data patterns.
Why This Course?
Designed for absolute beginners (no advanced math or ML required)
Visual, simple, and intuitive teaching style
Real datasets, hands-on practice
Includes cutting-edge AI tools (ChatGPT, Manus)
You’ll Walk Away With:
A complete toolkit for transforming raw data into powerful model inputs.
Working knowledge of feature selection, missing data handling, PCA, and more.
Experience using AI tools like Manus and ChatGPT to save time and boost creativity.
Confidence to tackle any ML project with cleaner, smarter data.
