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Sherif A. Tawfik Abbas
By the end of this project, you will learn how to perform the entire time series analysis workflow for the daily COVID-19 deaths. This workflow includes the following steps: how to examine time series data, prepare the data for analysis, train different models and test their performance, and finally use the models to forecast into the future. You will learn how to visualize data using the matplotlib library, extract features from a time series data set, and perform data splitting and normalization. You will create time series analysis models using the python programming language. You will create and train four time series models:...
Read more
By the end of this project, you will learn how to perform the entire time series analysis workflow for the daily COVID-19 deaths. This workflow includes the following steps: how to examine time series data, prepare the data for analysis, train different models and test their performance, and finally use the models to forecast into the future. You will learn how to visualize data using the matplotlib library, extract features from a time series data set, and perform data splitting and normalization. You will create time series analysis models using the python programming language. You will create and train four time series models:...
Read more
By the end of this project, you will learn how to perform the entire time series analysis workflow for the daily COVID-19 deaths. This workflow includes the following steps: how to examine time series data, prepare the data for analysis, train different models and test their performance, and finally use the models to forecast into the future. You will learn how to visualize data using the matplotlib library, extract features from a time series data set, and perform data splitting and normalization. You will create time series analysis models using the python programming language. You will create and train four time series models: SARIMAX, Facebook prophet, neural networks and XGBOOST.
Register for this course and see more details by visiting:
OpenCourser.com/course/ks76ai/compare
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Helps learners improve their data analysis skills
Offers a hands-on approach for students to develop their data science knowledge
Suitable for students interested in data analysis and machine learning
Provides a comprehensive overview of time series analysis techniques
Course duration may vary depending on a student's learning pace
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Reviews summary
Time series analysis for covid-19
This course provides a comprehensive overview of the time series analysis workflow for COVID-19 deaths. It covers data examination, preparation, modeling, and forecasting with Python. However, some learners found the pace too fast and the notebooks empty, while others had issues with the Colab environment.
Course provides informative material
"...informative..."
Instructor is excellent
"...Excellent instructor!..."
Colab environment can be clunky
"...the built-in Colab notebook was clunky and there was a time limit on using it!..."
Pace can be too fast
"...Please write some parts of the code on the next project, because the pace is too fast..."
Missing explanation on how to get prediction values
"...But at the end, the instructor should mention how should we get the prediction values in original units. Currently the predicted values are the values after twice differencing, and not the original values."
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 Compare time series predictions of COVID-19 deaths with these
activities:
Time Series Analysis Course Materials
Show steps
Compiling and reviewing your course materials will help you stay organized and focused throughout the course.
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-
Download and save all course materials.
-
Create a study schedule.
Python Programming
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Refreshing your Python programming skills will help you better understand the code examples and assignments in this course.
Browse courses on
Python Programming
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-
Review the basics of Python syntax and data structures.
-
Practice writing simple Python programs.
Time Series Analysis Study Group
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Participating in a study group is a great way to collaborate with other students, discuss course concepts, and reinforce your learning.
Show steps
-
Find a few classmates to form a study group.
-
Meet regularly to discuss course topics.
-
Work together on assignments and projects.
One other activity
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Time Series Data Visualization Using Matplotlib
Show steps
Visualizing time series data will help you analyze the trends, patterns, and seasonality of the data. This is a critical skill for understanding and forecasting time series data.
Show steps
-
Explore the Matplotlib library for time series visualization.
-
Plot different types of time series data such as line plots, scatter plots, and bar plots.
-
Customize the appearance of your plots by changing the colors, markers, and labels.
Time Series Analysis Course Materials
Show steps
Compiling and reviewing your course materials will help you stay organized and focused throughout the course.
Show steps
Show steps
Show steps
- Download and save all course materials.
- Create a study schedule.
Python Programming
Show steps
Refreshing your Python programming skills will help you better understand the code examples and assignments in this course.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Review the basics of Python syntax and data structures.
- Practice writing simple Python programs.
Time Series Analysis Study Group
Show steps
Participating in a study group is a great way to collaborate with other students, discuss course concepts, and reinforce your learning.
Show steps
Show steps
Show steps
- Find a few classmates to form a study group.
- Meet regularly to discuss course topics.
- Work together on assignments and projects.
One other activity
Expand to see all activities and additional details
Show all four activities
Time Series Data Visualization Using Matplotlib
Show steps
Visualizing time series data will help you analyze the trends, patterns, and seasonality of the data. This is a critical skill for understanding and forecasting time series data.
Show steps
Show steps
Show steps
- Explore the Matplotlib library for time series visualization.
- Plot different types of time series data such as line plots, scatter plots, and bar plots.
- Customize the appearance of your plots by changing the colors, markers, and labels.
Career center
Learners who complete Compare time series predictions of COVID-19 deaths will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to help businesses make better decisions. This course can help you develop the skills you need to become a successful Data Analyst by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Data Analysts who want to help businesses make informed decisions about the future.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models. This course can help you develop the skills you need to become a successful Machine Learning Engineer by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Machine Learning Engineers who want to develop models that can make accurate predictions.
Data Scientist
Data Scientist
A Data Scientist is responsible for using data to solve business problems. This course can help you develop the skills you need to become a successful Data Scientist by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Data Scientists who want to help businesses make informed decisions about the future.
Statistician
Statistician
A Statistician is responsible for collecting, analyzing, and interpreting data. This course can help you develop the skills you need to become a successful Statistician by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Statisticians who want to help businesses make informed decisions about the future.
Financial Analyst
Financial Analyst
A Financial Analyst is responsible for analyzing financial data to make recommendations about investments. This course can help you develop the skills you need to become a successful Financial Analyst by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Financial Analysts who want to make accurate predictions about the future performance of investments.
Actuary
Actuary
An Actuary is responsible for assessing and managing financial risk. This course can help you develop the skills you need to become a successful Actuary by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Actuaries who want to accurately assess and manage financial risk.
Epidemiologist
Epidemiologist
An Epidemiologist is responsible for studying the causes and spread of diseases. This course can help you develop the skills you need to become a successful Epidemiologist by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Epidemiologists who want to accurately predict the spread of diseases and develop effective prevention strategies.
Biostatistician
Biostatistician
A Biostatistician is responsible for applying statistical methods to medical data. This course can help you develop the skills you need to become a successful Biostatistician by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Biostatisticians who want to accurately predict the outcomes of medical treatments and develop effective prevention strategies.
Market Researcher
Market Researcher
A Market Researcher is responsible for collecting and analyzing data about markets and customers. This course can help you develop the skills you need to become a successful Market Researcher by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Market Researchers who want to accurately predict future market trends and develop effective marketing strategies.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst is responsible for using mathematical and analytical techniques to solve business problems. This course can help you develop the skills you need to become a successful Operations Research Analyst by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Operations Research Analysts who want to accurately predict future demand and develop effective operational strategies.
Risk Manager
Risk Manager
A Risk Manager is responsible for identifying, assessing, and managing risks. This course can help you develop the skills you need to become a successful Risk Manager by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Risk Managers who want to accurately predict future risks and develop effective risk management strategies.
Business Analyst
Business Analyst
A Business Analyst is responsible for analyzing business needs and developing solutions to improve business processes. This course can help you develop the skills you need to become a successful Business Analyst by providing you with a foundation in time series analysis. You will learn how to use different time series models to forecast future outcomes, which is a valuable skill for Business Analysts who want to accurately predict future business trends and develop effective business strategies.
Data Engineer
Data Engineer
A Data Engineer is responsible for designing, building, and maintaining data pipelines. This course may help you develop the skills you need to become a successful Data Engineer by providing you with a foundation in time series analysis. However, this course does not cover all of the skills that are required to be a successful Data Engineer, so you may need to supplement this course with other learning resources.
Software Engineer
Software Engineer
A Software Engineer is responsible for designing, developing, and maintaining software applications. This course may help you develop the skills you need to become a successful Software Engineer by providing you with a foundation in time series analysis. However, this course does not cover all of the skills that are required to be a successful Software Engineer, so you may need to supplement this course with other learning resources.
Web Developer
Web Developer
A Web Developer is responsible for designing and developing websites. This course may help you develop the skills you need to become a successful Web Developer by providing you with a foundation in time series analysis. However, this course does not cover all of the skills that are required to be a successful Web Developer, so you may need to supplement this course with other learning resources.
For more career information including salaries, visit:
OpenCourser.com/course/ks76ai/compare
Reading list
We've selected ten 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
Compare time series predictions of COVID-19 deaths.
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Classic text on time series analysis and forecasting. It covers a wide range of topics, including time series decomposition, model selection, and forecasting evaluation.
Save
Provides a practical guide to forecasting, with a focus on the use of statistical methods. It covers a wide range of topics, including time series decomposition, model selection, and forecasting evaluation.
Save
Provides a comprehensive introduction to time series analysis with a focus on applications in R. It covers a wide range of topics, including time series decomposition, stationarity testing, model selection, and forecasting.
Provides a comprehensive introduction to time series analysis using R software. It covers a wide range of topics, including time series decomposition, stationarity testing, model selection, and forecasting.
Provides a comprehensive introduction to time series analysis with a focus on modern techniques. It covers a wide range of topics, including time series decomposition, stationarity testing, model selection, and forecasting.
Provides a comprehensive introduction to time series analysis for the social sciences. It covers a wide range of topics, including time series decomposition, stationarity testing, model selection, and forecasting.
Provides a comprehensive introduction to time series analysis and forecasting, with a focus on the use of R software. It covers a wide range of topics, including time series decomposition, stationarity testing, model selection, and forecasting.
Save
Provides a comprehensive introduction to time series analysis and its applications, with a focus on the use of R software. It covers a wide range of topics, including time series decomposition, stationarity testing, model selection, and forecasting.
Save
Provides a practical guide to time series analysis and forecasting, with a focus on the use of statistical methods. It covers a wide range of topics, including time series decomposition, model selection, and forecasting evaluation.
Provides a comprehensive introduction to time series analysis and its applications, with a focus on the use of R software. It covers a wide range of topics, including time series decomposition, stationarity testing, model selection, and forecasting.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ks76ai/compare
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Sherif A. Tawfik Abbas
Good to know
Helps learners improve their data analysis skills
Offers a hands-on approach for students to develop their data science knowledge
Suitable for students interested in data analysis and machine learning
Provides a comprehensive overview of time series analysis techniques
Course duration may vary depending on a student's learning pace
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