Basic Course Description
This course is for you if you want to have a real feel of the clustering algorithms without having to learn all the complicated maths. Additionally, this course is also for you if you have had previous hours and hours of classroom theory on the subject but could never got a change or figure out how to implement and solve data science problems with it.
The approach in this course is very practical and we will start everything from very scratch. We will immediately start coding after a couple of introductory tutorials and we try to keep the theory to bare minimal. All the coding will be done in Python which is one of the fundamental programming languages for engineer and science students and is frequently used by top data science research groups world wide.
Below is the brief outline of this course.
Segment 1: Introduction to course
Segment 2: KMeans Clustering
Segment 3: Mean Shift Clustering
Segment 4: DBSCAN Clustering
Segment 5: Hierarchical Clustering
Segment 6: HDBSCAN Clustering
Segment 7: Applications of Clustering
Your Benefits and Advantages:
If you do not find the course useful, you are covered with 30 day money back guarantee, full refund, no questions asked!
You will be sure of receiving quality contents since the instructors has already many courses on Data Science on udemy.
You have lifetime access to the course.
You have instant and free access to any updates i add to the course.
You have access to all Questions and discussions initiated by other students.
You will receive my support regarding any issues related to the course.
Check out the curriculum and Freely available lectures for a quick insight.
How to implement different clustering algorithms in python
How to handle issues of varying cluster sizes, densities, shapes and noise
When to use a specific algorithm
Take away code templates
You should have a little know how of python and jupytor
Python must be installed on your computer