Table of Contents
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
- Explore
Description
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.
Who this course is for:
- Beginners in Data Science and Machine Learning
- spiring Machine Learning Practitioners:
- Anyone Curious About Data
How to Get this course FREE?
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