Organisations all around the world are using data to predict behaviours and extract valuable real-world insights to inform decisions. Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government.
Offered By
University of London
Goldsmiths, University of London
Foundations of Data Science: K-Means Clustering in Python
University of LondonAbout this Course
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Shareable Certificate
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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
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
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 Clustering
- Machine Learning
- Programming 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
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Offered by
University of London
The University of London is a federal University which includes 18 world leading Colleges. Our distance learning programmes were founded in 1858 and have enriched the lives of thousands of students, delivering high quality University of London degrees wherever our students are across the globe. Our alumni include 7 Nobel Prize winners. Today, we are a global leader in distance and flexible study, offering degree programmes to over 50,000 students in over 180 countries. To find out more about studying for one of our degrees where you are, visit www.london.ac.uk
Goldsmiths, University of London
Championing research-rich degrees that provoke thought, stretch the imagination and tap into tomorrow’s world, at Goldsmiths we’re asking the questions that matter now in subjects as diverse as the arts and humanities, social sciences, cultural studies, computing, and entrepreneurial business and management. We are a community defined by its people: innovative in spirit, analytical in approach and open to all.
Syllabus - What you will learn from this course
7 hours to complete
Week 1: Foundations of Data Science: K-Means Clustering in Python
This week we will introduce you to the course and to the team who will be guiding you through the course over the next 5 weeks. The aim of this week's material is to gently introduce you to Data Science through some real-world examples of where Data Science is used, and also by highlighting some of the main concepts involved.
7 hours to complete
9 videos (Total 22 min)
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
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
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
Reviews
- 5 stars72.62%
- 4 stars21.55%
- 3 stars3.66%
- 2 stars1.29%
- 1 star0.86%
TOP REVIEWS FROM FOUNDATIONS OF DATA SCIENCE: K-MEANS CLUSTERING IN PYTHON
by MPSep 12, 2020
It was a well-taught course. I felt that during the final project-making, students were not spoon-fed, instead, pushed us to become more creative.
by MPJan 2, 2022
This course was excellent. Though I already knew the concepts in this course and the programing skills, it has inspired me to 100% take the MSC provided. Excellent lectures. Just Excellent.
by NCMay 16, 2020
This course gives us a good balance between theory and practice. I wish there was an intermediate or advanced level to continue.
by PSJun 24, 2021
A Great course which successfully marries both the mathematical/statistical foundations for K-Means and also its implementation in Python.
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