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Data Mining Through Cluster Analysis Using Python

Discover two non-hierarchical clustering algorithms, k-means and DBSCAN.
2.9
2.9/5
(96 reviews)
2,818 students
Created by

6.6

CourseMarks Score®

5.5

Freshness

5.0

Feedback

8.8

Content

Platform: Udemy
Video: 58m
Language: English
Next start: On Demand

Top Cluster Analysis courses:

Detailed Analysis

CourseMarks Score®

6.6 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

5.5 / 10
This course was last updated on 11/2017.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

5.0 / 10
We analyzed factors such as the rating (2.9/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

8.8 / 10
Video Score: 7.7 / 10
The course includes 58m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 3 hours 51 minutes of 11 Cluster Analysis courses on Udemy.
Detail Score: 8.7 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

3 articles.
6 resources.
0 exercise.
0 tests or quizzes.

Table of contents

Description

This course is ideal for those that are interested in data mining, and it is a beginner course. You should have a beginner to intermediate understanding of Python as I don’t spend a lot of time on the programming aspect.

Most data in the world (whether text,audio,visual, etc) is raw or unlabeled. This is precisely the reason that unsupervised machine learning has become so important. By using certain approaches to unsupervised machine learning (like clustering) we can discover patterns or underlying structures in data. This is a major component of exploratory data mining. Furthermore, when one does exploratory data mining, it is used to draw hypotheses, assess assumptions about our statistical inferences, and its used as a basis for further research. For example, the conclusion of a cluster analysis could result in the initiation of a full scale experiment.
The course covers two of the most important and common non-hierarchical clustering algorithms, K-means and DBSCAN using Python. 
With K-Means, we start with a ‘starter’ (or simple) example. We then discuss ‘Completeness Score’. The next lesson we discuss how k-means deals with larger variances and different shapes. Then we discuss ‘Color Quantization’. This is used when an individual wants to decrease the size of an image/and or see if there is any underlying structure to an image. Finally, we will take a look at cells of the human body, and do some cell segmentation. For DBSCAN, we will look at a starter example as well using Blobs. Then I will show you how DBSCAN overcomes some of the issues of K-means.
If you are interested in data mining, and want to get a taste of how it works, this course is a great introduction!

You will learn

✓ Apply kmeans clustering
✓ Apply DBSCAN clustering
✓ Appreciate and understand the purpose of unsupervised machine learning

Requirements

• Understanding Python at beginner or intermediate level is mandatory.

This course is for

• Students interested in clustering techniques and unsupervised machine learning
• Interest in data mining and/or data analysis

How much does the Data Mining Through Cluster Analysis Using Python course cost? Is it worth it?

The course costs $14.99. And currently there is a 25% discount on the original price of the course, which was $19.99. So you save $5 if you enroll the course now.
The average price is $12.1 of 11 Cluster Analysis courses on Udemy.

Does the Data Mining Through Cluster Analysis Using Python course have a money back guarantee or refund policy?

YES, Data Mining Through Cluster Analysis Using Python has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Data Mining Through Cluster Analysis Using Python course, but there is a $5 discount from the original price ($19.99). So the current price is just $14.99.

Who is the instructor? Is Ermin Dedic a SCAM or a TRUSTED instructor?

Ermin Dedic has created 20 courses that got 5,984 reviews which are generally positive. Ermin Dedic has taught 46,049 students and received a 4.4 average review out of 5,984 reviews. Depending on the information available, Ermin Dedic is a TRUSTED instructor.
All Things Data.
I have a passion for anything data, whether it is applying statistical methods to data more generally, or utilizing a data-driven approach in the Healthcare or Finance/Banking industries.

I studied Psychology for 6-years, including 2 years of Graduate school, where I was training to be a Child/School Psychologist. I was fortunate enough to have the opportunity to experience a blend of course work and clinical work but also recognize some of the problems facing the mental health system and graduate school system. While I am very interested in finding a solution for the latter, this is a long-term goal.

I did ultimately decide to voluntarily leave the Grad program, it was via academics that I fell in love with statistics and statistical software like SPSS/SAS.

Furthermore, it was my Graduate school experience that not only solidified my interest in teaching, it’s where I received a lot of positive feedback on my ability to break down complex topics.

I enjoy receiving messages from students who have passed exams, obtained interviews, or gained employment, from taking one of my courses.

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Para meus alunos de língua portuguesa …

Sou apaixonado por estatística, ciência de dados, programação orientada a objetos e psicologia / saúde mental. Eu desenvolvi um conhecimento em Programação e Estatística SAS através da minha escolaridade e auto-estudo. Também sou autodidata em programação orientada a objetos.




Eu sou um ex-aluno de graduação em psicologia educacional. Dois anos depois, decidi me retirar voluntariamente. Aprendi que o ambiente acadêmico tradicional e o ambiente clínico não eram o caminho adequado para promover mudanças em larga escala.




Ensinar é uma paixão há muito tempo. Criei meu primeiro curso de vídeo online em 2016 (um curso de Estatística). Foi um projeto de pura paixão. Como resultado de obter ótimos comentários, continuei! Atualmente, ensino os cursos de SAS, estatísticas e psicologia, mas também estou sempre aprendendo. Gosto de receber mensagens de alunos que passaram nos exames, obtiveram entrevistas ou obtiveram emprego ao fazer um de meus cursos.

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6.6

CourseMarks Score®

5.5

Freshness

5.0

Feedback

8.8

Content

Platform: Udemy
Video: 58m
Language: English
Next start: On Demand

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