Time Series is a mathematical concept that consists of data points indexed
according to a timed order. A Time-Series can also be defined as a sequence of
events taken at successive equally spaced points in time. In Time Series
Analysis, we analyze a sequence of data points collected over an interval of
time. You should be able to record data points at consistent intervals over a
set period. This is different from just recording data points at random
intervals. A Time Series Analysis can show how different variables change over time. It
provides an additional source of information and a set order of dependencies
between the data. Time Series data can also be used for forecasting and
predicting future data based on historical data.
There are a vast number of courses, tutorials, classes, certifications, and
online training that you can access to get a mastery over Time Series Analysis.
We have done the hard job for you and whittled down that enormous list to just
six courses; the cream of the crop.
You will get access to video lectures, graded assignments, quizzes, and questionnaires.
You will learn about the random walk model, the noise model, and autocorrelation functions.
Course Duration: 11 hours
Different organizations use Time Series Analysis to learn about the underlying
trends and systematic patterns over time. These trends can then be visualized
using modern analytics platforms for better understanding. They can also be
used to predict the likelihood of future events.
Today's technology allows us to collect a vast amount of data and it is easier
than ever to collect enough data for a comprehensive analysis.
Some uses of
Time Series Analysis include weather forecasting, rainfall measurements,
temperature data, quarterly sales, stock prices, industry forecasts, and
interest rates.
6 Best Courses to Learn Time Series Analysis in 2025
This list contains a mixture of free as well as paid courses, and courses
suited for all levels of experience; whether you are at a beginner level,
intermediate, or advanced, we have selected just the correct course for
you.
Check out the list below.
Check out the list below.
1. Time Series Analysis in Python [Udemy]
Rating: 4.6 stars out of 5
Overview
This course will work as your stepping stone into the fascinating world of Time Series Analysis using Python. In this course, you will learn about the basics of Data Science and how to unlock the powerful features of Python.
You will also learn about the important packages used in Python for Time
Series Analysis, visualization methods, from theory to modelling. You will
also learn about vector models, GARCH, SARIMAX, Auto ARIMA, and forecasting
methods.
This course was created by 365Careers, which is one of the most popular instructors on Udemy.
This course was created by 365Careers, which is one of the most popular instructors on Udemy.
Despite being a beginner course and requiring no prior experience with Time
Series Analysis, this can be useful for learners on all levels.
You will learn how to relate Data Science Techniques in Python to real-life examples and visualize Time Series data.
You will become competent in Machine Learning and be able to predict future values from a set of data.
Course Duration: 7.5 hours
You will learn how to relate Data Science Techniques in Python to real-life examples and visualize Time Series data.
You will become competent in Machine Learning and be able to predict future values from a set of data.
Course Duration: 7.5 hours
2. Python for Time Series Data Analysis [Udemy]
Rating: 4.7 stars out of 5
Overview
This is one of the best courses on Python for time Series Data Analysis that you will find on the internet. This course will help you learn the Python programming language from the ground up, and you will receive the know-how on using Python for forecasting Time Series data.
You will also learn how to use pandas, Numpy, and Statsmodels for Time
Series Forecasting and Analysis.
Jose Portilla, who is the instructor of this course, is the Head of Data Science at Pierian Data Inc. and is one of the most popular instructors on the platform. He will guide you through each step as you make the rewarding journey of learning Python for Time Series Data Analysis.
Jose Portilla, who is the instructor of this course, is the Head of Data Science at Pierian Data Inc. and is one of the most popular instructors on the platform. He will guide you through each step as you make the rewarding journey of learning Python for Time Series Data Analysis.
You will learn how to manipulate data in Python using the pandas and Numpy
libraries. You will be able to create time-stamped data and create
visualizations using pandas. This course also includes the Facebook Prophet
Library, which can be used for forecasting the future using Time Series
Data.
Course Duration: 15.5 hours
Course Duration: 15.5 hours
3. Practical Time Series Analysis with Suny Online [Coursera]
Rating: 4.6 stars out of 5
Overview
This course is designed for someone at an intermediate level and is intended for people with a certain level of technical competency and who are looking to deepen their understanding of the topic. You will experiment with datasets that represent sequential information, like stock prices, agricultural output, and annual rainfall.
You will learn how to represent data graphically and forecast the future
based on the present variables. This course is designed by the professors at
the State University of New York, who will keep in touch with you throughout
the course to clear your doubts.
You will also receive a shareable certificate upon completion of the course.
Students will get access to free video tutorials as well as the related
written materials, and gain an understanding of crucial topics by attempting
quizzes.
Students will learn about different mathematical models that will help them
in processing different kinds of data.
Students will be introduced to the SARIMA model of forecasting.
Course Duration: 26 hours
This is an open course that is designed by the professors at the Lazy
Programmer Team. This is a graduate-level course, which combines a survey of
the theory behind Time Series Analysis with the applications of this
analysis in econometric methods.
Students will be introduced to the SARIMA model of forecasting.
Course Duration: 26 hours
4. Time Series Analysis, Forecasting, And Machine Learning [Udemy]
Overview
This is an open course that is designed by the professors at the Lazy
Programmer Team. This is a graduate-level course, which combines a survey of
the theory behind Time Series Analysis with the applications of this
analysis in econometric methods.
This will help you in developing the necessary skills for doing empirical
research using Time Series data. You will also be assisted with additional
video lectures, downloadable resource content, practice sessions, and
quizzes.
Real-world projects will help you in understanding the complexity of Time
Series Analysis as a subject. You will learn about models of estimation and
interference in persistent time series, the Maximum Likelihood and the
Bayesian approaches, structural breaks, univariate stationery, and
non-stationary models, and frequency domain methods.
You will learn about the interferences of Modern Dynamic Stochastic General
Equilibrium Models on the subject of Macroeconomics.
Course Duration: 22.5 hours
Udemy is a platform that hosts a plethora of courses related to the field of
Data Science. This course has been designed by some of the best instructors
on the platform. You will get access to a highly interactive course that
will introduce you to the core theory behind the concept of Time Series
Analysis and techniques.
Course Duration: 22.5 hours
5. Time Series Analysis and Forecasting with Python [Udemy]
Overview
Udemy is a platform that hosts a plethora of courses related to the field of
Data Science. This course has been designed by some of the best instructors
on the platform. You will get access to a highly interactive course that
will introduce you to the core theory behind the concept of Time Series
Analysis and techniques.
The course is divided into five chapters, and you will learn how to organize
and visualize Time Series data in R. You will also learn about some common
assumptions and characteristics of a financial Time Series.
You will get access to video lectures, graded assignments, quizzes, and questionnaires.
You will learn about the random walk model, the noise model, and autocorrelation functions.
Course Duration: 11 hours
Conclusion
Time Series Analysis is important because Time Series forecasting is
important. Business forecasting, understanding past behaviour, and
planning for the future, especially for policymakers rely heavily on Time
Series Analysis.
These courses will help you learn about modelling, moving averages, simple
exponential smoothing, Holt's linear trend model, Auto Regression
Integrated Moving Average (ARIMA), SARIMAX, etc.
If you liked this list of Top 5 Courses to Learn Time Series Analysis, why
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