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
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own 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

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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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