Data Mining Fundamentals

3 lessons

11 Videos

2 Hours

Overview

The Data Mining fundamentals series is jam-packed with all the background information, technical terminology, and basic knowledge that you will need to hit the ground running.

In this course, you will:

  • What data is, the basic vocabulary and data attributes
  • Data quality, data noise, missing values and data preprocessing, known as data cleaning
  • Different strategies used in data mining such as data aggregation and data sampling
  • Feature selection
  • Various evaluation measures
  • Data Visualization using various plots

Course Contents

1. Fundamentals of Data Mining

  • Basic Vocabulary
  • Data Attributes
  • Data Attributes (Cont.)
  • Basic Data Types

2. Datasets for Data Mining

  • Transaction Data & Document Data
  • Ordered Data & Graph Data

3. Data Issues in Data Mining

  • Data Quality
  • Data Noise

4. Data Preprocessing & Transformation

  • Missing Values and Duplicated Data
  • Data Cleaning
  • Data Aggregation
  • Data Sampling
  • Data Sampling Types
  • Dimensionality Reduction
  • Data Transformation
  • Feature Selection

5. Evaluation Measures

  • Similarity and Dissimilarity
  • Euclidean Distance & Cosine Similarity
  • Evaluating Correlation
  • Center and Spread Measurement
  • Summary Statistics

6. Data Visualization & Exploration

  • Data Visualization & Exploration
  • Histograms & Box Plots
  • Scatter Plots & Contour Plots