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COVID-19
Les séries temporelles avec Python et Pandas
ELINGUI Pascal Uriel
ELINGUI Pascal Uriel
Dans ce projet guidé, vous manipulerez des séries temporelles avec Python et Pandas. Une série temporelle est une suite de valeurs numériques représentant l'évolution d'une quantité spécifique au cours du temps. Les données du COVID-19 en sont un parfait exemple que nous allons explorer dans ce projet guidé.
Read more
Dans ce projet guidé, vous manipulerez des séries temporelles avec Python et Pandas. Une série temporelle est une suite de valeurs numériques représentant l'évolution d'une quantité spécifique au cours du temps. Les données du COVID-19 en sont un parfait exemple que nous allons explorer dans ce projet guidé.
Read more
Dans ce projet guidé, vous manipulerez des séries temporelles avec Python et Pandas. Une série temporelle est une suite de valeurs numériques représentant l'évolution d'une quantité spécifique au cours du temps. Les données du COVID-19 en sont un parfait exemple que nous allons explorer dans ce projet guidé.
La grande majorité des données que nous exploitons sont des séries temporelles. Savoir les manipuler efficacement est un prérequis obligatoire pour tous professionnel des données. (Data Scientist, Data Analyst, Data Engineer, Ingénieur Big Data, etc)
Vous expérimentez plusieurs techniques pour indexer, filtrer, agréger, échantillonner et afficher des séries temporelles en python
Register for this course and see more details by visiting:
OpenCourser.com/course/mw9ekt/covid
What's inside
Syllabus
Project Overview
Dans ce projet guidé, vous manipulerez des séries temporelles avec Python et Pandas. Une série temporelle est une suite de valeurs numériques représentant l'évolution d'une quantité spécifique au cours du temps. Les données du COVID-19 en sont un parfait exemple que nous allons explorer dans ce projet guidé.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Well suited for data professionals looking to enhance their time series manipulation skills
Covers key techniques for working with time series data in Python, including indexing, filtering, aggregation, sampling, and visualization
Leverages real-world COVID-19 data for practical examples and relevance
Taught by experienced instructors in the field of data science
Suitable for learners who have prior experience in Python and data handling
May require additional resources or background knowledge for beginners in data science
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Reviews summary
Recommended covid-19 time series python pandas
This course on manipulating COVID-19 time series data with Python Pandas is well received by students. They particularly appreciate the practical exercises and well-structured content.
structured content
"...well-structured content."
practical exercises
"...practical exercises..."
Activities
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We're preparing activities for
COVID-19 : Les séries temporelles avec Python et Pandas.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete COVID-19 : Les séries temporelles avec Python et Pandas will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists apply computational and analytical approaches to solve complex problems and extract meaningful insights from large datasets. A course in COVID-19 Time Series with Python and Pandas may enhance your data analysis skills and equip you with the necessary knowledge to manage and interpret COVID-19 related data. The course's focus on time series analysis, indexing, filtering, and aggregation of data can benefit Data Scientists aiming to understand and make predictions based on time-dependent data.
Data Analyst
Data Analyst
Data Analysts utilize various techniques to examine data patterns and trends, and communicate insights to stakeholders. The course in COVID-19 Time Series with Python and Pandas aligns with the role of a Data Analyst, as it provides practical experience in handling COVID-19 time series data. Understanding data manipulation, visualization, and forecasting techniques covered in the course can enhance your analytical abilities and enable you to derive valuable insights from data.
Data Engineer
Data Engineer
Data Engineers design, build, and manage data pipelines to ensure data quality and availability. A course in COVID-19 Time Series with Python and Pandas can be beneficial for Data Engineers as it provides hands-on experience in data preprocessing, data cleaning, and data transformation. The course also covers techniques for data visualization, which is essential for communicating data insights to stakeholders.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. A course in COVID-19 Time Series with Python and Pandas can be relevant for Quantitative Analysts as it provides a foundation in time series analysis and forecasting techniques. The course's focus on data manipulation and visualization can also be beneficial for understanding and presenting financial data.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models for various applications. A course in COVID-19 Time Series with Python and Pandas may be useful for Machine Learning Engineers as it provides a foundation in data manipulation, feature engineering, and model evaluation. The course's focus on time series analysis can also be relevant for building predictive models based on time-dependent data.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes and patterns of health and disease within populations. A course in COVID-19 Time Series with Python and Pandas can be relevant for Epidemiologists as it provides hands-on experience in handling COVID-19 related data. The course's focus on data analysis, visualization, and forecasting can assist Epidemiologists in understanding disease trends, identifying risk factors, and developing prevention strategies.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to analyze biological and medical data. A course in COVID-19 Time Series with Python and Pandas may be useful for Biostatisticians as it provides a foundation in time series analysis and data visualization. The course's focus on handling COVID-19 data can also be relevant for understanding and analyzing epidemiological data.
Public Health Analyst
Public Health Analyst
Public Health Analysts use data to identify and address public health issues. A course in COVID-19 Time Series with Python and Pandas can be relevant for Public Health Analysts as it provides experience in handling and analyzing COVID-19 related data. The course's focus on data visualization and forecasting can assist Public Health Analysts in communicating data insights to stakeholders and developing evidence-based public health policies.
Health Data Analyst
Health Data Analyst
Health Data Analysts analyze healthcare data to improve patient outcomes and healthcare delivery. A course in COVID-19 Time Series with Python and Pandas may be useful for Health Data Analysts as it provides a foundation in data manipulation, data visualization, and forecasting. The course's focus on handling COVID-19 data can also be relevant for understanding and analyzing healthcare data in general.
Business Analyst
Business Analyst
Business Analysts use data to solve business problems and improve organizational performance. A course in COVID-19 Time Series with Python and Pandas may be useful for Business Analysts as it provides a foundation in data manipulation and data visualization. The course's focus on handling COVID-19 data can also be relevant for understanding and analyzing business data in sectors affected by the pandemic.
Financial Analyst
Financial Analyst
Financial Analysts use data to analyze financial performance and make investment recommendations. A course in COVID-19 Time Series with Python and Pandas may be useful for Financial Analysts as it provides a foundation in data manipulation and data visualization. The course's focus on handling COVID-19 data can also be relevant for understanding and analyzing financial data in sectors affected by the pandemic.
Actuary
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. A course in COVID-19 Time Series with Python and Pandas may be useful for Actuaries as it provides a foundation in data manipulation and data visualization. The course's focus on handling COVID-19 data can also be relevant for understanding and analyzing actuarial data in sectors affected by the pandemic.
Statistician
Statistician
Statisticians use mathematical and statistical methods to analyze data and draw conclusions. A course in COVID-19 Time Series with Python and Pandas may be useful for Statisticians as it provides a foundation in data manipulation and data visualization. The course's focus on handling COVID-19 data can also be relevant for understanding and analyzing statistical data in sectors affected by the pandemic.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists create visual representations of data to communicate insights and trends. A course in COVID-19 Time Series with Python and Pandas may be useful for Data Visualization Specialists as it provides a foundation in data manipulation and data visualization. The course's focus on handling COVID-19 data can also be relevant for understanding and visualizing data in sectors affected by the pandemic.
Research Analyst
Research Analyst
Research Analysts gather, analyze, and interpret data to inform decision-making. A course in COVID-19 Time Series with Python and Pandas may be useful for Research Analysts as it provides a foundation in data manipulation and data visualization. The course's focus on handling COVID-19 data can also be relevant for understanding and analyzing research data in sectors affected by the pandemic.
For more career information including salaries, visit:
OpenCourser.com/course/mw9ekt/covid
Reading list
We've selected eight 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
COVID-19 : Les séries temporelles avec Python et Pandas.
Save
Ce livre classique sur l'analyse des séries temporelles fournit une couverture complète des méthodes théoriques et pratiques. Il est utile à la fois comme référence et comme manuel pour les étudiants et les praticiens.
Save
Ce livre pratique se concentre sur les méthodes de prévision des séries temporelles. Il couvre un large éventail de techniques, des méthodes traditionnelles aux approches modernes basées sur l'apprentissage automatique.
Ce livre fournit une introduction complète à Python pour l'analyse des données. Il couvre les concepts fondamentaux, les outils et les techniques pour manipuler, analyser et visualiser les données, y compris les séries temporelles.
Save
Ce livre se concentre sur l'analyse des séries temporelles dans R. Il couvre un large éventail de méthodes, des techniques classiques aux approches modernes basées sur R.
Ce livre fournit une introduction à l'analyse des séries temporelles à l'aide de R. Il couvre les concepts fondamentaux et les méthodes pour manipuler, analyser et modéliser les séries temporelles.
Cet autre livre classique sur l'analyse des séries temporelles fournit une couverture complète des méthodes théoriques et pratiques. Il est utile à la fois comme référence et comme manuel pour les étudiants et les praticiens.
Save
Ce livre se concentre sur les méthodes statistiques pour l'analyse des séries temporelles. Il couvre les techniques classiques, telles que les modèles ARIMA et les tests de stationnarité.
Ce livre fournit une introduction accessible à l'analyse des séries temporelles et à la prévision. Il couvre les concepts fondamentaux, les méthodes et les applications dans divers domaines.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/mw9ekt/covid
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Effort
70
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
ELINGUI Pascal Uriel
Language
Français
Good to know
Well suited for data professionals looking to enhance their time series manipulation skills
Covers key techniques for working with time series data in Python, including indexing, filtering, aggregation, sampling, and visualization
Leverages real-world COVID-19 data for practical examples and relevance
Taught by experienced instructors in the field of data science
Suitable for learners who have prior experience in Python and data handling
May require additional resources or background knowledge for beginners in data science
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