Coursera Time Series Analysis Courses List

Coursera offers a range of Time Series Analysis courses to help learners gain a comprehensive understanding of the subject. These courses cover topics such as forecasting, time series decomposition, and ARIMA models. Learners can benefit from the interactive learning environment and the expertise of experienced instructors. With Coursera, learners can gain the skills and knowledge needed to analyze time series data.

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19 Related Courses

for Coursera Time Series Analysis Courses
Free

Sequences Time Series and Prediction

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5/5
Coursera Coursera 274 274 learners
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This course, Sequences Time Series and Prediction, is part of the deeplearning.ai TensorFlow Specialization. It will teach you how to use TensorFlow to build time series models and apply them to real-world data. You will learn best practices for preparing time series data, and how to use RNNs and 1D ConvNets for prediction. With this course, you will gain the skills to build AI-powered algorithms that are scalable and can be applied to real-world problems. View all

Free

The Econometrics of Time Series Data

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5.0/5
Coursera Coursera 127 127 learners
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This course will provide you with the knowledge and skills to understand and apply econometric models to time series data. You will learn about stationary and non-stationary models, and how to test for non-stationarity. You will also explore the applications of time series models, forecasting exercises, and models for changing volatility. With the help of real financial market data, you will be able to estimate and interpret the empirical autocorrelation function, cointegration equations, and ARCH(p) and GARCH(p,q) models. By the end of this course, you will be able to confidently manipulate and plot data, and perform in-sample and out-of-sample forecasting exercises. View all

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Free

Specialized Models: Time Series and Survival Analysis

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5.0/5
Coursera Coursera
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This course provides an introduction to specialized models in Machine Learning, such as Time Series Analysis and Survival Analysis. Through hands-on activities, participants will learn best practices for analyzing data with a time component and censored data, as well as verifying assumptions derived from Statistical Learning. View all

Free

Practical Time Series Analysis

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4.0/5
Coursera Coursera
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This course, Practical Time Series Analysis, is designed for people with some technical competencies who need to concentrate on the routine sorts of presentation and analysis that deepen the understanding of their professional topics. It covers data sets that represent sequential information, such as stock prices, annual rainfall, sunspot activity, the price of agricultural products, and more. It also looks at mathematical models and graphical representations that provide insights into the data, as well as how to make forecasts. The language used is R, a free implementation of the S language. With video lectures, supporting written materials, quizzes, and discussion with fellow learners, this course is a great way to learn Time Series Analysis. View all

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Intro to Time Series Analysis in R

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5.0/5
Coursera Coursera 170 170 learners
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This course is perfect for anyone looking to learn the basics of time series analysis in R. In just 2 hours, you will learn the essential theory and build each of the major model types to forecast the future. You will also gain an understanding of the essential packages and functions in R to make time series analysis easy. Sign up now and start your journey to becoming a time series analysis expert! View all

Time Series Data Visualization And Analysis Techniques

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4.0/5
Coursera Coursera
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This course provides an in-depth exploration of time series data visualization and analysis techniques. Learn how to use line charts, bar charts, and boxplots to detect outliers, key moments, and overall trends. Discover how color mapping can help you gain a better understanding of your data. With this course, you will be able to analyze time series data with confidence. View all

Time Series Analysis (ARIMA) with R

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5.0/5
Coursera Coursera
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This project is perfect for anyone interested in learning the fundamentals of time series analysis using ARIMA. Through this project, you will gain a comprehensive understanding of the concepts of time series analysis and its application in R Studio. You will learn to identify the components of time series data, conduct diagnostic tests, and evaluate model process and orders. Finally, you will be able to forecast future values with the best fit model. View all

Exploratory Time Series Analysis

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4.0/5
Coursera Coursera
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This project is perfect for beginners who want to learn about time series data analysis using Python. It covers the basics of importing libraries and data sets, getting descriptive statistics, visualizing data, and applying transformation functions to convert non-stationary to stationary. With this project, you will gain the skills to effectively build models and get insight into the data set. Start your journey to becoming a time series data analysis expert today! View all

Time Series Forecasting and ARIMA Models in Python

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5.0/5
Coursera Coursera
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This project-based course is perfect for anyone interested in learning how to use ARIMA models for time series analysis and forecasting. With the help of Python, you will learn how to do basic statistical tests for time series and apply them to different datasets. By the end of the course, you will have a better understanding of time series concepts and be able to analyze different datasets. Don't miss out on this great opportunity to learn how to use ARIMA models for time series forecasting! View all

Free

Modeling Time Series and Sequential Data

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5.0/5
Coursera Coursera 110 110 learners

Learn the basics of Modeling Time Series and Sequential Data View all

Free

Demand Forecasting Using Time Series

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4.0/5
Coursera Coursera 94 94 learners

Discover the fundamentals of Demand Forecasting Using Time Series View all

Forecasting Univariate Time Series with an LSTM

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5.0/5
Coursera Coursera

Learn the basics of Forecasting Univariate Time Series with an LSTM View all

Compare time series predictions of COVID-19 deaths

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4.0/5
Coursera Coursera

Explore the essentials of Compare time series predictions of COVID-19 deaths View all

Time series forecasting with Prophet

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5.0/5
Coursera Coursera

Get a comprehensive overview of Time series forecasting with Prophet View all

Simulating Time Series Data by Parallel Computing in Python

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4.0/5
Coursera Coursera

Learn the basics of Simulating Time Series Data by Parallel Computing in Python View all

Series temporales con Facebook' Prophet y NeuralProphet

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4.0/5
Coursera Coursera

En este proyecto aplicado y práctico aprenderás a utilizar Prophet y neuralProphet. View all

Series Temporales con Pycaret y Python

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4.0/5
Coursera Coursera

En este proyecto aplicado y práctico aprenderás a entrenar modelos capaces de predecir series temporales. Para ello utilizaremos la librería de Pycaret con Python y entrenaremos modelos como: XGBoost, Catboost o Random forest. También aprenderemos a generar modelos más avanzados con lñas diferentes técnicas de ensamblado de modelos. View all

Einfuhrung in Zeitreihenanalyse mit R

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5.0/5
Coursera Coursera

In diesem zweistündigen Projekt wirst du eine gründliche Analyse einer Zeitreihe mithilfe eines ARIMA-Modells durchführen. Dieses Projekt erklärt die grundlegenden Konzepte von Zeitreihenanalyse und illustriert dies praktisch in RStudio. Wir beschreiben die Arten von Zeitreihen und ihre verschiedenen Komponenten. Das Projekt deckt ab, wie man diagnostische Tests durchführt, um die grundlegenden Vorraussetzungen für ARIMA-Modelle zu testen. Schließlich leiten wir das beste Modell ab, um zukünftige Werte vorherzusagen. Wir werden gemeinsam die grundlegenden Pakete und Funktionen in R durchgehen, um Zeitreihenanalyse einfach zu machen. Du benötigst für dieses Projekt keine Vorkenntnisse! Wir werden alles Schritt für Schritt erklären. View all

Free

Creating Features for Time Series Data

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4.0/5
Coursera Coursera 115 115 learners

Discover the fundamentals of Creating Features for Time Series Data View all

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