Introduction to Data Science
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An Introduction to Data
Data science is a field of study that focuses on techniques and algorithms to extract knowledge from data. The area combines data mining and machine learning with data-specific domains. This section focuses on defining "data" before going to any complicated topic.
Data Dimensionality and Space
This section's focus is on defining the common terminology widely used in data science. The video lectures in this section focus on terms like objects, data points, features, dimensions, vectors, high-dimensional data, and mathematical space.
Proximity in Data Science Context
Many data mining and machine learning algorithms rely on distance or similarity between objects/data points. Video lectures in this section focus on standard proximity measures used in data science. The section also explains how to use proximity measures to examine the neighborhood of a given point.
A large portion of data science focuses on exploratory analysis. Scientists and practitioners use statistical techniques to understand the data. One way to explore the data is to check if there are clusters of data points. A cluster is a group of data points that have similar features. This section explains the clustering algorithms.
- What is clustering?
- Quiz: introduction to clustering
- A few types of clustering algorithms
- k-means clustering algorithm
- Hierarchical Agglomerative Clustering (HAC) algorithm (under construction)
- Density-based clustering algorithm: DBSCAN (under construction)
- Evaluation of clustering algorithms: Measure the quality of a clustering outcome
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- Lectures 22
- Quizzes 4
- Students 763
- Assessments Yes
Review for course
This course is best for fresher is data sciences to learn about data science.