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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.

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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.

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What's inside

Syllabus

COVID19 Data Analysis Using Python
By the end of this project, you will learn how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. in this Course, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consisting 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.

Good to know

Know what's good
, what to watch for
, 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

Covid-19 data analysis basics

Learners say this beginner-friendly COVID-19 data analysis course is well-received, featuring engaging assignments and a knowledgeable instructor. The course largely positive reviews highlight the practical skills gained from working with real-world data, including data cleaning, analysis, and visualization. However, some learners have reported minor technical issues with the platform and have suggested improvements to the course structure.
Learners develop practical skills in data analysis, including data cleaning, manipulation, and visualization using Python libraries.
"The project os compact and merge programming with analysis, but it's easy if you have python programming experience."
"Got to learn -a well-versed approach to data analysis -also got very interested in the topic -professor was very awesome"
"T​he tasks were easy and they helped me review my skills in Python programming and data analysis. The instructor gave very clear instructions and enough time for practice."
This course is designed for beginners and provides a solid foundation in data analysis concepts and techniques. Learners with little or no prior experience in data analysis can benefit from this course.
"Beautiful designed course. Great instructor, in fact, the best among the guided projects I've completed so far. Recommended."
"If You are new to Data Science, This course will help you to understand Data manipulation using Pandas,and also plotting them "
"This course is educative and intuitive, the tutor explained each step taken. I recommend it for all, either beginner or expert data science. "
The instructor is praised for their clear explanations, engaging teaching style, and ability to break down complex concepts into understandable terms.
"The knowledge in this course is very practical, and the teacher teaches in detail. I'd recommend this course to build the basics."
"I really enjoyed this class. The only problem is the application used which is not very practical. Kernel is slow and it's very complicated for Mac users."
"I found the instructor very helpful and through with the concepts. Would love to join another project with perhaps more advanced data analysis ."
This course offers a hands-on project that guides learners through the analysis of COVID-19 data using Python libraries like Pandas, NumPy, and Matplotlib.
"Very Friendly Project for the Beginners."
"This project is really good!! Far better than that lightening speed INTRODUCTION to Data Science course. Learnt a lot!! Thanks Mr.Ahmad!!🙏"
"This course is educative and intuitive, the tutor explained each step taken."
Some learners have reported technical difficulties with the platform used for the hands-on assignments, such as slow cloud desktop performance and issues with the Rhyme environment.
"The platform is very compacted and educative for interested python users at the very beginning. "
"my cloud is not working it has been two days i have been writting in the chat box but no one replied"
"The Rhyme Environment was very poor. It was not at all stable especially with a slower internet. "
The course structure is generally well-paced and easy to follow. However, some learners have encountered minor technical difficulties with the platform used for the hands-on assignments.
"I couldn't like the tool "Rhyme". The cloud desktop was quite slow but overall it was a fine experience"
"One star is not given because of the cloud timelimit. I think the project could be taught via non cloud platform way."
"This guided project is very well structured and easy to follow. Highly recommended for beginners to gain valuable hands-on exposure in python programming and Data Analysis."

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
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
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
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
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
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

Career center

Learners who complete COVID19 Data Analysis Using Python will develop knowledge and skills that may be useful to these careers:
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 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 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 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 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 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
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
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 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 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 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 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 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 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
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.

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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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