Gain insights into data science fundamentals, explore machine learning and big data, and delve into real-time projects. Discover systematic approaches to data acquisition, wrangling, and solving diverse problems.

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There is a lot of dispersed, and somewhat conflicting information on the internet when it comes to data science, making it tough to know where to start. Don't worry. 

This course will get you familiar with the state of data science and the related fields such as machine learning and big data. You will be going through the fundamental concepts and libraries which are essential to solve any problem in this field. 

You will work on real-time projects from Kaggle while also honing your mathematical skills which will be used extensively in most problems you face. You will also be taken through a systematic approach to learning about data acquisition to data wrangling and everything in between. This is your all-in-one guide to becoming a confident data scientist.

An Introductory Guide to Data Science and Machine Learning

# Unsupervised Learning

Unsupervised learning refers to the type of Machine Learning that draws inferences from the dataset that is not labeled. This contrasts with supervised learning where we dealt with labeled datasets.

## Types of Unsupervised learning

1. Unsupervised learning helps us identify patterns in the dataset. Data clustering is one of the techniques of unsupervised learning, where elements in a single cluster have the same properties and are assigned the same label. Some of the most famous clustering algorithms include 

* **KMeans** Clustering 

* **Hierarchical** Clustering

* **DBSCAN** Clustering.



Unsupervised learning is a type of Machine Learning, and it plays a vital role in solving many real world problems. You will learn about it in this lesson.

What is Data Science ?

Applications of Data Science

Overview of Libraries

Probability and Statistics

Machine Learning Part-1

Machine Learning Part-2

Machine Learning Part-3

Deep Learning

Machine Learning Tools and Libraries

Big Data Tools and Technologies

Where to go next ?

Unsupervised Learning

Unsupervised Learning