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Ahmad Varasteh
In this project, you will learn how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consist of various life factors, scored by the people living in each country around the globe. We are going to merge these two datasets to see if there is any relationship between the spread of the virus in a country and how happy people are, living in that country.
Read more
In this project, you will learn how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consist of various life factors, scored by the people living in each country around the globe. We are going to merge these two datasets to see if there is any relationship between the spread of the virus in a country and how happy people are, living in that country.
Read more
In this project, you will learn how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consist of various life factors, scored by the people living in each country around the globe. We are going to merge these two datasets to see if there is any relationship between the spread of the virus in a country and how happy people are, living in that country.
Notes: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/5t3b0y/covid19
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What's inside
Syllabus
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Provides a foundation in COVID19 data analysis using Python
Suitable for someone based in the North America region
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Reviews summary
Applied covid19 data analysis with python
According to the course outline, learners can expect a hands-on project-based experience focused on COVID19 data analysis using Python. Students will learn to preprocess and merge real-world datasets from John Hopkins University on confirmed cases and various life factors to explore the relationship between virus spread and national happiness. This project is particularly geared towards those seeking practical application of Python skills in data science. A key consideration is that the project is optimized for learners in the North America region, which may affect the experience for international participants.
Develops essential data preprocessing and merging.
"I learned robust methods for data preprocessing and merging in Python."
"The course provided me with solid foundational skills in preparing data for analysis."
"I now feel more confident in tackling raw datasets and getting them ready for insights."
Utilizes relevant COVID19 and life factor data.
"I appreciated working with actual COVID19 data from John Hopkins University."
"The use of real-world datasets on happiness factors made the analysis feel relevant."
"I gained insight into applying data analysis to contemporary global challenges."
Offers practical, applied learning through a project.
"I loved the hands-on approach to analyzing real-world data."
"The project structure made learning Python for data analysis very practical for me."
"I found the direct application of concepts through the project highly beneficial."
Optimized for North American learners.
"I note that the project provides the best experience for North America-based learners."
"Learners outside North America might need to consider potential regional data nuances."
"I understand the course content is specifically geared towards a North American context."
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 COVID19 Data Analysis Using Python with these
activities:
Form a study group with other learners taking the course
Show steps
Enhance understanding and retention of course material by forming a study group with other learners.
Show steps
-
Identify potential study partners within the course
-
Set up regular meetings
-
Discuss course material, share notes, and work on assignments together
Follow tutorials on COVID19 data analysis
Show steps
Gain additional insights on COVID19 data analysis by following guided tutorials.
Show steps
-
Search for tutorials on COVID19 data analysis
-
Select a tutorial that aligns with your learning goals
-
Follow the instructions in the tutorial
-
Apply what you learned to your own project
Practice using Python libraries for data manipulation
Show steps
Strengthen understanding of Python libraries for data manipulation by completing practice drills.
Browse courses on
Python
Show steps
-
Install the necessary Python libraries
-
Find practice problems or exercises online
-
Solve the problems using Python libraries
Two other activities
Expand to see all activities and additional details
Show all five activities
Visualize COVID19 data for a specific country
Show steps
Solidify knowledge of data preprocessing and merging by visualizing the COVID19 data for a specific country.
Show steps
-
Choose a country of interest
-
Download the COVID19 and life factors datasets
-
Preprocess and merge the datasets
-
Create a visualization of the data
Write a blog post about COVID19 data analysis
Show steps
Deepen understanding of COVID19 data analysis by writing a blog post that shares your insights and findings.
Browse courses on
Data Visualization
Show steps
-
Choose a specific topic within COVID19 data analysis
-
Research and gather data on the topic
-
Analyze the data and draw insights
-
Write a blog post that clearly and effectively communicates your findings
Form a study group with other learners taking the course
Show steps
Enhance understanding and retention of course material by forming a study group with other learners.
Show steps
Show steps
Show steps
- Identify potential study partners within the course
- Set up regular meetings
- Discuss course material, share notes, and work on assignments together
Follow tutorials on COVID19 data analysis
Show steps
Gain additional insights on COVID19 data analysis by following guided tutorials.
Show steps
Show steps
Show steps
- Search for tutorials on COVID19 data analysis
- Select a tutorial that aligns with your learning goals
- Follow the instructions in the tutorial
- Apply what you learned to your own project
Practice using Python libraries for data manipulation
Show steps
Strengthen understanding of Python libraries for data manipulation by completing practice drills.
Browse courses on
Python
Show steps
Show steps
Show steps
- Install the necessary Python libraries
- Find practice problems or exercises online
- Solve the problems using Python libraries
Two other activities
Expand to see all activities and additional details
Show all five activities
Visualize COVID19 data for a specific country
Show steps
Solidify knowledge of data preprocessing and merging by visualizing the COVID19 data for a specific country.
Show steps
Show steps
Show steps
- Choose a country of interest
- Download the COVID19 and life factors datasets
- Preprocess and merge the datasets
- Create a visualization of the data
Write a blog post about COVID19 data analysis
Show steps
Deepen understanding of COVID19 data analysis by writing a blog post that shares your insights and findings.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a specific topic within COVID19 data analysis
- Research and gather data on the topic
- Analyze the data and draw insights
- Write a blog post that clearly and effectively communicates your findings
Career center
Learners who complete COVID19 Data Analysis Using Python will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
As a Data Analyst, you will be responsible for collecting, cleaning, and analyzing data to identify trends and patterns. This course will help you develop the skills you need to succeed in this role, including data visualization, statistical analysis, and machine learning. By learning how to work with real-world datasets, you will be well-prepared to enter the field of data analysis.
Data Scientist
Data Scientist
Data Scientists use their skills in mathematics, statistics, and computer science to extract insights from data. This course will help you develop the foundational skills you need to become a Data Scientist, including data wrangling, data mining, and machine learning. By learning how to work with real-world datasets, you will be well-prepared to enter the field of data science.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. This course will help you develop the skills you need to succeed in this role, including data engineering, model building, and model deployment. By learning how to work with real-world datasets, you will be well-prepared to enter the field of machine learning engineering.
Data Engineer
Data Engineer
Data Engineers build and maintain the infrastructure that supports data analysis and machine learning. This course will help you develop the skills you need to succeed in this role, including data warehousing, data pipelines, and data governance. By learning how to work with real-world datasets, you will be well-prepared to enter the field of data engineering.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course will help you develop the skills you need to succeed in this role, including financial modeling, risk analysis, and portfolio optimization. By learning how to work with real-world datasets, you will be well-prepared to enter the field of quantitative finance.
Business Analyst
Business Analyst
Business Analysts use data to solve business problems. This course will help you develop the skills you need to succeed in this role, including data analysis, business intelligence, and project management. By learning how to work with real-world datasets, you will be well-prepared to enter the field of business analysis.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This course will help you develop the skills you need to succeed in this role, including data visualization, statistical modeling, and data mining. By learning how to work with real-world datasets, you will be well-prepared to enter the field of statistics.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes of disease and develop strategies to prevent and control them. This course will help you develop the skills you need to succeed in this role, including data analysis, statistical modeling, and public health. By learning how to work with real-world datasets, you will be well-prepared to enter the field of epidemiology.
Public Health Analyst
Public Health Analyst
Public Health Analysts collect, analyze, and interpret data to improve the health of populations. This course will help you develop the skills you need to succeed in this role, including data analysis, epidemiology, and health policy. By learning how to work with real-world datasets, you will be well-prepared to enter the field of public health.
Health Data Scientist
Health Data Scientist
Health Data Scientists use their skills in data science to improve the health of populations. This course will help you develop the skills you need to succeed in this role, including data analysis, machine learning, and health informatics. By learning how to work with real-world datasets, you will be well-prepared to enter the field of health data science.
Health Economist
Health Economist
Health Economists use economic principles to analyze the health care system. This course will help you develop the skills you need to succeed in this role, including data analysis, health policy, and economics. By learning how to work with real-world datasets, you will be well-prepared to enter the field of health economics.
Health Policy Analyst
Health Policy Analyst
Health Policy Analysts use data to inform health policy decisions. This course will help you develop the skills you need to succeed in this role, including data analysis, health policy, and public health. By learning how to work with real-world datasets, you will be well-prepared to enter the field of health policy analysis.
Health Informatics Specialist
Health Informatics Specialist
Health Informatics Specialists use their skills in information technology to improve the health care system. This course will help you develop the skills you need to succeed in this role, including data analysis, health informatics, and project management. By learning how to work with real-world datasets, you will be well-prepared to enter the field of health informatics.
Clinical Data Manager
Clinical Data Manager
Clinical Data Managers oversee the collection, storage, and analysis of clinical data. This course will help you develop the skills you need to succeed in this role, including data management, clinical research, and project management. By learning how to work with real-world datasets, you will be well-prepared to enter the field of clinical data management.
Biostatistician
Biostatistician
Biostatisticians use statistical methods to analyze biological data. This course will help you develop the skills you need to succeed in this role, including data analysis, statistical modeling, and bioinformatics. By learning how to work with real-world datasets, you will be well-prepared to enter the field of biostatistics.
For more career information including salaries, visit:
OpenCourser.com/course/5t3b0y/covid19
Reading list
We've selected 16 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
COVID19 Data Analysis Using Python.
Provides a comprehensive overview of the COVID-19 pandemic, from its origins in Wuhan, China, to its global impact. It covers the scientific, social, and economic aspects of the pandemic, and offers insights into how we can prepare for future pandemics.
Provides a historical perspective on pandemics, and argues that we can learn from the past to better prepare for the future. It covers a wide range of pandemics, from the Black Death to the Spanish Flu, and offers insights into how we can prevent and control future pandemics.
Explores the origins of pandemics, and argues that we need to do more to prevent future pandemics from occurring. It covers a wide range of animal-borne diseases, and offers insights into how we can reduce the risk of future pandemics.
Save
Provides a detailed account of the 1918 influenza pandemic, which killed an estimated 50 million people worldwide. It covers the scientific, social, and economic aspects of the pandemic, and offers insights into how we can prepare for future pandemics.
Save
Explores the emergence of new infectious diseases, and argues that we need to do more to prepare for future pandemics. It covers a wide range of emerging diseases, and offers insights into how we can reduce the risk of future pandemics.
Provides a detailed account of the Ebola virus outbreak in 1989. It covers the scientific, social, and political aspects of the outbreak, and offers insights into how we can prevent future outbreaks.
Save
Explores the potential for global catastrophic risks, and argues that we need to do more to reduce the risk of these risks occurring. It covers a wide range of global catastrophic risks, including pandemics, nuclear war, and climate change.
Save
Explores the potential for existential risks, and argues that we need to do more to reduce the risk of these risks occurring. It covers a wide range of existential risks, including pandemics, nuclear war, and climate change.
Save
Explores the potential risks and benefits of artificial intelligence, and argues that we need to do more to ensure that AI is used for good. It covers a wide range of topics related to AI, including the potential for AI to cause pandemics.
Save
Explores the potential future of humanity, and argues that we are on the cusp of a new era of technological progress. It covers a wide range of topics, including the potential for artificial intelligence, genetic engineering, and space exploration.
Provides a comprehensive overview of world history, from the ancient world to the present day. It covers a wide range of topics, including the rise and fall of civilizations, the development of science and technology, and the role of religion in human history.
Explores the science of habit formation, and argues that we can use our understanding of habits to improve our lives and businesses. It covers a wide range of topics, including the role of habits in our daily lives, the power of habit stacking, and the importance of breaking bad habits.
Save
This novel tells the story of a sudden epidemic of blindness that strikes a city. It explores the themes of social collapse, human nature, and the importance of human connection.
Save
This novel tells the story of a group of survivors of a global pandemic. It explores the themes of hope, resilience, and the human spirit.
Provides a comprehensive overview of human history, from our origins as a species to the present day. It covers a wide range of topics, including the rise of agriculture, the development of cities, and the emergence of global capitalism.
Save
This novel tells the story of a bubonic plague outbreak in the Algerian city of Oran. It explores the themes of existentialism, absurdity, and the human condition.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5t3b0y/covid19
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