Module 2: Data Mining & Preprocessing | KTU FDS | Data Cleaning, Integration & Visualization

Описание: Welcome to Module 2 of Foundation of Data Science (KTU Syllabus)! 🎓
In this video, we explore the core concepts of Data Mining and Preprocessing — the essential steps that prepare raw data for meaningful analysis. This lesson is perfect for KTU students, data science beginners, and anyone aiming to understand the data preparation process in depth.

📚 Topics Covered (KTU Module 2):
✅ Introduction to Data Mining
✅ Kinds of Data Mining
✅ What is Data Preprocessing?
✅ Understanding Data Quality
✅ Need for Data Preprocessing
✅ Major Tasks in Data Preprocessing
✅ Data Cleaning – Handling Missing Values & Noisy Data
✅ Data Cleaning as a Process
✅ Data Integration
✅ Data Reduction
✅ Data Transformation & Data Discretization
✅ Introduction to Data Visualization

💡 Learn How To:

Improve data quality through cleaning and transformation

Handle missing and inconsistent data effectively

Combine and simplify datasets using integration and reduction techniques

Understand the role of visualization in data analysis

🛠️ Tools & Techniques:
Excel | Python | Pandas | Matplotlib | Power BI

🎯 Ideal For:

KTU B.Tech students

Data Science & AI beginners

Anyone preparing for KTU exams or interviews

📺 Watch till the end for clear examples and visual explanations of each concept!
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