About this Course

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Beginner Level

You will need mathematical and statistical knowledge and skills at least at high-school level.

Approx. 29 hours to complete
English

What you will learn

  • Define and explain the key concepts of data clustering

  • Demonstrate understanding of the key constructs and features of the Python language.

  • Implement in Python the principle steps of the K-means algorithm.

  • Design and execute a whole data clustering workflow and interpret the outputs.

Skills you will gain

K-Means ClusteringMachine LearningProgramming in Python
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level

You will need mathematical and statistical knowledge and skills at least at high-school level.

Approx. 29 hours to complete
English

Offered by

Placeholder

University of London

Placeholder

Goldsmiths, University of London

Syllabus - What you will learn from this course

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Week
1

Week 1

7 hours to complete

Week 1: Foundations of Data Science: K-Means Clustering in Python

7 hours to complete
9 videos (Total 22 min)
Week
2

Week 2

4 hours to complete

Week 2: Means and Deviations in Mathematics and Python

4 hours to complete
11 videos (Total 37 min), 4 readings, 11 quizzes
Week
3

Week 3

8 hours to complete

Week 3: Moving from One to Two Dimensional Data

8 hours to complete
16 videos (Total 53 min), 10 readings, 15 quizzes
Week
4

Week 4

4 hours to complete

Week 4: Introducing Pandas and Using K-Means to Analyse Data

4 hours to complete
8 videos (Total 37 min), 6 readings, 8 quizzes

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