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Ryan Ahmed
In this case study, we will train an unsupervised machine learning algorithm to cluster countries based on features such as economic production, social support, life expectancy, freedom, absence of corruption, and generosity.
Read more
In this case study, we will train an unsupervised machine learning algorithm to cluster countries based on features such as economic production, social support, life expectancy, freedom, absence of corruption, and generosity.
Read more
In this case study, we will train an unsupervised machine learning algorithm to cluster countries based on features such as economic production, social support, life expectancy, freedom, absence of corruption, and generosity.
The World Happiness Report determines the state of global happiness. The happiness scores and rankings data has been collected by asking individuals to rank their life from 0 (worst possible life) to 10 (best possible life).
Register for this course and see more details by visiting:
OpenCourser.com/course/zeypzi/k
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Syllabus
Clustering: World Happiness Report
In this case study, we will train an unsupervised machine learning algorithm to cluster countries based on features such as economic production, social support, life expectancy, freedom, absence of corruption, and generosity.
The World Happiness Report determines the state of global happiness. The happiness scores and rankings data has been collected by asking individuals to rank their life from 0 (worst possible life) to 10 (best possible life).
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Uses real-world data and case studies for each concept, which is standard in educational psychology and is likely to improve retention and comprehension of advanced topics
The course is taught by Ryan Ahmed, who is an expert in data science, machine learning and deep learning
Suitable for students whose work would involve the analysis of large datasets such as researchers, economists, analysts, data scientists and machine learning engineers
Save this course
Save K-Means Clustering 101: World Happiness Report to your list so you can find it easily later:
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Reviews summary
Informative k-means course
According to students, this course is an informative introduction to the K-Means clustering algorithm. Learners say that it is a well-structured course with engaging assignments and slides that are easy to follow. Students also mention that a basic understanding of Python is recommended. Overall, this course is a good option for those looking to learn more about K-Means clustering.
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in K-Means Clustering 101: World Happiness Report with these
activities:
Create a Course Summary
Show steps
Improve retention by organizing and summarizing course materials.
Show steps
-
Review the course notes.
-
Highlight the key points.
-
Create a summary document.
R Programming Review
Show steps
Refreshing your R programming skills will ensure that you can effectively analyze data and complete course assignments.
Browse courses on
R Programming
Show steps
-
Review basic R syntax and data structures.
-
Practice data manipulation and analysis using R packages.
-
Complete練習 sets or small projects to reinforce your skills.
Review K-Means Clustering
Show steps
Reduce friction by refreshing prerequisite knowledge and skills to gain a stronger baseline when the course begins.
Browse courses on
K-Means
Show steps
-
Find a tutorial on K-Means clustering.
-
Follow the tutorial step-by-step.
-
Try out the code examples provided in the tutorial.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Connect with a Clustering Expert
Show steps
Gain additional guidance and insights from an experienced professional.
Browse courses on
Clustering
Show steps
-
Identify potential mentors.
-
Reach out to mentors and request their guidance.
-
Schedule regular meetings or calls.
Connect with Experts
Show steps
Seeking guidance from experts in the field will provide valuable insights and support.
Browse courses on
Mentorship
Show steps
-
Identify potential mentors who work in the field of happiness research or data science.
-
Reach out to them and express your interest in mentorship.
-
Attend networking events or workshops where you can connect with professionals.
Community Involvement
Show steps
Engaging with the community will provide hands-on experience and a deeper understanding of the factors influencing happiness.
Browse courses on
Volunteering
Show steps
-
Identify volunteer opportunities related to mental health or well-being.
-
Participate in community events that promote happiness and social connections.
-
Share your experiences and insights with your classmates.
Review World Happiness Report
Show steps
Grasping the key concepts and findings of the World Happiness Report will provide a strong foundation for understanding the course material.
View
The Ages of Globalization
on Amazon
Show steps
-
Read the Executive Summary of the World Happiness Report.
-
Review the methodology used to calculate the happiness scores.
-
Identify the factors that contribute to happiness according to the report.
Discussion Forum Participation
Show steps
Engaging in discussions with peers will provide diverse perspectives and stimulate your thinking on course concepts.
Show steps
-
Pose thoughtful questions related to the course material.
-
Respond to questions and comments from other students.
-
Reflect on the discussions and apply insights to your learning.
Analyze Clustering Results
Show steps
Solidify learning by reinforcing concepts and skills taught in the course.
Browse courses on
Clustering Analysis
Show steps
-
Download the dataset from the course website.
-
Apply the K-Means clustering algorithm to the dataset.
-
Evaluate the results of the clustering.
-
Write a report summarizing your findings.
Clustering Exercise
Show steps
Strengthening your understanding of clustering techniques through practice will enhance your ability to apply them in the course project.
Browse courses on
Clustering
Show steps
-
Implement a simple K-Means clustering algorithm in Python.
-
Apply the algorithm to a dataset of countries.
-
Analyze the results of the clustering and identify patterns.
Data Visualization Exploration
Show steps
Gaining proficiency in data visualization will enhance your ability to communicate your analysis effectively.
Browse courses on
Data Visualization
Show steps
-
Follow tutorials on data visualization tools such as Tableau or Power BI.
-
Create interactive visualizations based on the happiness data.
-
Share your visualizations and insights with others.
Visualize the Clustering Results
Show steps
Enhance understanding by creating a visual representation of the data.
Browse courses on
Data Visualization
Show steps
-
Choose a data visualization tool.
-
Create a visualization of the clustering results.
-
Analyze the visualization to identify patterns and insights.
Research Paper Exploration
Show steps
Delving into research papers on happiness and well-being will enrich your understanding of the course material and foster critical thinking skills.
Show steps
-
Identify a research paper related to the course topic.
-
Read and analyze the paper.
-
Summarize the key findings and implications of the paper.
Develop a Clustering Application
Show steps
Test and solidify skills by applying them to a real-world problem.
Browse courses on
Clustering
Show steps
-
Define the problem and gather the data.
-
Choose a clustering algorithm.
-
Implement the clustering algorithm.
-
Test and evaluate the application.
Participate in a Clustering Hackathon
Show steps
Push limits and gain recognition by participating in a competitive event.
Browse courses on
Clustering
Show steps
-
Find a clustering hackathon.
-
Form a team or work independently.
-
Develop a clustering solution.
-
Present your solution to the judges.
Create a Course Summary
Show steps
Improve retention by organizing and summarizing course materials.
Show steps
Show steps
Show steps
- Review the course notes.
- Highlight the key points.
- Create a summary document.
R Programming Review
Show steps
Refreshing your R programming skills will ensure that you can effectively analyze data and complete course assignments.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Review basic R syntax and data structures.
- Practice data manipulation and analysis using R packages.
- Complete練習 sets or small projects to reinforce your skills.
Review K-Means Clustering
Show steps
Reduce friction by refreshing prerequisite knowledge and skills to gain a stronger baseline when the course begins.
Browse courses on
K-Means
Show steps
Show steps
Show steps
- Find a tutorial on K-Means clustering.
- Follow the tutorial step-by-step.
- Try out the code examples provided in the tutorial.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Connect with a Clustering Expert
Show steps
Gain additional guidance and insights from an experienced professional.
Browse courses on
Clustering
Show steps
Show steps
Show steps
- Identify potential mentors.
- Reach out to mentors and request their guidance.
- Schedule regular meetings or calls.
Connect with Experts
Show steps
Seeking guidance from experts in the field will provide valuable insights and support.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Identify potential mentors who work in the field of happiness research or data science.
- Reach out to them and express your interest in mentorship.
- Attend networking events or workshops where you can connect with professionals.
Community Involvement
Show steps
Engaging with the community will provide hands-on experience and a deeper understanding of the factors influencing happiness.
Browse courses on
Volunteering
Show steps
Show steps
Show steps
- Identify volunteer opportunities related to mental health or well-being.
- Participate in community events that promote happiness and social connections.
- Share your experiences and insights with your classmates.
Review World Happiness Report
Show steps
Grasping the key concepts and findings of the World Happiness Report will provide a strong foundation for understanding the course material.
View
The Ages of Globalization
on Amazon
Show steps
Show steps
Show steps
- Read the Executive Summary of the World Happiness Report.
- Review the methodology used to calculate the happiness scores.
- Identify the factors that contribute to happiness according to the report.
Discussion Forum Participation
Show steps
Engaging in discussions with peers will provide diverse perspectives and stimulate your thinking on course concepts.
Show steps
Show steps
Show steps
- Pose thoughtful questions related to the course material.
- Respond to questions and comments from other students.
- Reflect on the discussions and apply insights to your learning.
Analyze Clustering Results
Show steps
Solidify learning by reinforcing concepts and skills taught in the course.
Browse courses on
Clustering Analysis
Show steps
Show steps
Show steps
- Download the dataset from the course website.
- Apply the K-Means clustering algorithm to the dataset.
- Evaluate the results of the clustering.
- Write a report summarizing your findings.
Clustering Exercise
Show steps
Strengthening your understanding of clustering techniques through practice will enhance your ability to apply them in the course project.
Browse courses on
Clustering
Show steps
Show steps
Show steps
- Implement a simple K-Means clustering algorithm in Python.
- Apply the algorithm to a dataset of countries.
- Analyze the results of the clustering and identify patterns.
Data Visualization Exploration
Show steps
Gaining proficiency in data visualization will enhance your ability to communicate your analysis effectively.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Follow tutorials on data visualization tools such as Tableau or Power BI.
- Create interactive visualizations based on the happiness data.
- Share your visualizations and insights with others.
Visualize the Clustering Results
Show steps
Enhance understanding by creating a visual representation of the data.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a data visualization tool.
- Create a visualization of the clustering results.
- Analyze the visualization to identify patterns and insights.
Research Paper Exploration
Show steps
Delving into research papers on happiness and well-being will enrich your understanding of the course material and foster critical thinking skills.
Show steps
Show steps
Show steps
- Identify a research paper related to the course topic.
- Read and analyze the paper.
- Summarize the key findings and implications of the paper.
Develop a Clustering Application
Show steps
Test and solidify skills by applying them to a real-world problem.
Browse courses on
Clustering
Show steps
Show steps
Show steps
- Define the problem and gather the data.
- Choose a clustering algorithm.
- Implement the clustering algorithm.
- Test and evaluate the application.
Participate in a Clustering Hackathon
Show steps
Push limits and gain recognition by participating in a competitive event.
Browse courses on
Clustering
Show steps
Show steps
Show steps
- Find a clustering hackathon.
- Form a team or work independently.
- Develop a clustering solution.
- Present your solution to the judges.
Career center
Learners who complete K-Means Clustering 101: World Happiness Report will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist collects, analyzes, and interprets large amounts of data to uncover patterns, trends, and insights. This course in K-Means Clustering and the World Happiness Report may be useful for Data Scientists who want to gain a better understanding of how to use unsupervised machine learning algorithms to cluster data. The course can also help Data Scientists develop skills in data visualization and storytelling.
Market Researcher
Market Researcher
A Market Researcher collects and analyzes data to understand consumer behavior and market trends. This course in K-Means Clustering and the World Happiness Report may be useful for Market Researchers who want to learn how to use unsupervised machine learning algorithms to segment customers and identify target markets.
Public Policy Analyst
Public Policy Analyst
A Public Policy Analyst researches, analyzes, and develops public policies. This course in K-Means Clustering and the World Happiness Report may be useful for Public Policy Analysts who want to learn how to use unsupervised machine learning algorithms to identify and analyze social trends.
Social Scientist
Social Scientist
A Social Scientist studies human behavior and society. This course in K-Means Clustering and the World Happiness Report may be useful for Social Scientists who want to learn how to use unsupervised machine learning algorithms to analyze social data.
Economist
Economist
An Economist studies the production, distribution, and consumption of goods and services. This course in K-Means Clustering and the World Happiness Report may be useful for Economists who want to learn how to use unsupervised machine learning algorithms to analyze economic data and identify trends.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data to draw conclusions. This course in K-Means Clustering and the World Happiness Report may be useful for Statisticians who want to learn how to use unsupervised machine learning algorithms to analyze data and identify patterns.
Urban Planner
Urban Planner
An Urban Planner designs and plans the development of cities and towns. This course in K-Means Clustering and the World Happiness Reportmay be useful for Urban Planners who want to learn how to use unsupervised machine learning algorithms to analyze urban data and identify trends.
Computer Scientist
Computer Scientist
A Computer Scientist researches, designs, and develops computer systems and applications. This course in K-Means Clustering and the World Happiness Report may be useful for Computer Scientists who want to learn how to use unsupervised machine learning algorithms to analyze computer data and identify trends.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data to make investment recommendations. This course in K-Means Clustering and the World Happiness Report may be useful for Financial Analysts who want to learn how to use unsupervised machine learning algorithms to analyze financial data and identify trends.
Business Analyst
Business Analyst
A Business Analyst helps organizations to improve their performance by analyzing data and making recommendations. This course in K-Means Clustering and the World Happiness Report may be useful for Business Analysts who want to learn how to use unsupervised machine learning algorithms to analyze business data and identify trends.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical techniques to solve business problems. This course in K-Means Clustering and the World Happiness Report may be useful for Operations Research Analysts who want to learn how to use unsupervised machine learning algorithms to analyze data and identify patterns.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course in K-Means Clustering and the World Happiness Report may be useful for Software Engineers who want to learn how to use unsupervised machine learning algorithms to analyze software data and identify trends.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, and interprets data to uncover patterns, trends, and insights. This course in K-Means Clustering and the World Happiness Report may be useful for Data Analysts who want to gain a better understanding of how to use unsupervised machine learning algorithms to cluster data. The course can also help Data Analysts develop skills in data visualization and storytelling.
Management Consultant
Management Consultant
A Management Consultant helps organizations to improve their performance by analyzing data and making recommendations. This course in K-Means Clustering and the World Happiness Report may be useful for Management Consultants who want to learn how to use unsupervised machine learning algorithms to analyze data and identify trends.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products. This course in K-Means Clustering and the World Happiness Report may be useful for Product Managers who want to learn how to use unsupervised machine learning algorithms to analyze market data and identify trends.
For more career information including salaries, visit:
OpenCourser.com/course/zeypzi/k
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
K-Means Clustering 101: World Happiness Report.
Provides the latest research on the science of happiness, including the factors that contribute to happiness and the policies that can be implemented to promote it.
Conversation between the Dalai Lama and Desmond Tutu about joy, suffering, and the meaning of life. It powerful and inspiring read that will leave you with a sense of hope and optimism.
Save
Personal account of one woman's year-long journey to find more happiness in her life. It provides practical tips and advice that can be applied to anyone's life.
Save
Comprehensive overview of the field of positive psychology. It provides a detailed look at the research on happiness, well-being, and other positive emotions.
Provides a scientific approach to happiness, based on the latest research in positive psychology. It offers evidence-based strategies for increasing happiness and well-being.
Contains the Dalai Lama's teachings on happiness, compassion, and wisdom. It great resource for anyone looking for inspiration and guidance on how to live a more meaningful life.
Provides a comprehensive guide to happiness, based on the latest research in positive psychology and ancient wisdom traditions. It great resource for anyone who wants to learn more about happiness and how to achieve it.
Save
Provides a scientific overview of the factors that contribute to well-being. It great resource for anyone who wants to learn more about the science of happiness and how to apply it to their own life.
Provides evidence-based strategies for increasing happiness and productivity at work. It great resource for anyone looking to improve their workplace happiness.
Save
Explores the different types of happiness and provides a framework for achieving authentic happiness. It classic work in the field of positive psychology.
Provides a different perspective on happiness and challenges the idea that we need to be happy all the time. It offers strategies for dealing with negative emotions and living a more meaningful life.
Classic self-help book that provides simple and practical tips for changing your mindset and achieving greater happiness.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/zeypzi/k
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Effort
1.5 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Language
English
Good to know
Uses real-world data and case studies for each concept, which is standard in educational psychology and is likely to improve retention and comprehension of advanced topics
The course is taught by Ryan Ahmed, who is an expert in data science, machine learning and deep learning
Suitable for students whose work would involve the analysis of large datasets such as researchers, economists, analysts, data scientists and machine learning engineers
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