7 Best Time Series Courses Online in 2026 (Coursera, Udemy, and Free)

Are you looking for the Best Time Series Courses Online? If yes, this article is for you. In this article, I listed the Best Time Series Courses Online. So, give a few minutes to this article and find the best time series course for you.

Time series is a specific skill, predicting future values from data collected over time, sales, stock prices, weather, demand, and the right course depends on your level, on if you want the classical statistical methods (ARIMA and friends) or the modern deep learning approach, and on if you code in Python or R.

Quick answer before the detail. If you want the best all-round Coursera course, Practical Time Series Analysis from SUNY is the one most people should start with. If you want the deep learning approach with TensorFlow, take DeepLearning.AI’s Sequences, Time Series, and Prediction. If you want a free start, Udacity’s Time Series Forecasting course costs nothing. And if you want a cheap, own-it-forever deep dive, the Udemy time series courses go on sale for around $10 to $15. Let me break down all seven.

Now without further ado, let’s get started and find out some Best Time Series Courses Online–

Best Time Series Courses Online

What is time series analysis? (quick orientation)

Before the courses, a quick plain-English base, because it helps you pick the right one. A time series is just a set of measurements of the same thing taken at regular intervals over time, daily sales, hourly temperatures, monthly revenue. Time series analysis is finding the patterns in that data (the trend, the seasonality, the noise), and time series forecasting is using those patterns to predict what comes next.

There are two broad approaches, and courses tend to lean one way or the other. The classical statistical approach uses methods like ARIMA, exponential smoothing, and Holt-Winters, this is what most “time series analysis” courses teach. The modern machine learning and deep learning approach uses models like LSTMs and other neural networks to forecast, this is what the deep-learning-flavoured courses teach. Neither is “better,” they suit different problems, and the strongest learners understand both. So as you read the list, notice which approach each course takes, because that’s the real difference between them.

So how does forecasting actually work, in plain terms? Take monthly sales data. First you break it into pieces: the trend (is it generally going up or down over time?), the seasonality (does it spike every December?), and the noise (the random wobble left over). A forecasting model learns those pieces from your past data, then projects them forward to guess the next months. A classical model like ARIMA does this with statistics, looking at how each point relates to the ones before it. A deep learning model like an LSTM does it by learning the patterns through a neural network. Either way, the core idea is the same: find the repeating structure in the past, and extend it into the future. That’s forecasting in one paragraph, and every course below is teaching you a different way to do exactly that.

Best time series courses at a glance

S/N	Course	Platform	Best for	Approach	Price (verify)
1	Practical Time Series Analysis	Coursera (SUNY)	Best all-round start	Statistical (R)	~$49/mo, 7-day trial
2	Sequences, Time Series, and Prediction	Coursera (DeepLearning.AI)	Deep learning forecasting (~23h)	Deep learning (TensorFlow)	~$49/mo, 7-day trial
3	Time Series Forecasting	Udacity	A free start	Statistical	Free
4	Analyzing Time Series and Sequential Data Specialization	Coursera	Large-scale forecasting (SAS)	Statistical (SAS)	~$49/mo
5	Machine Learning for Trading	Udacity	Time series for finance	ML	Free (audit)
6	Time Series Analysis, Forecasting, and Machine Learning	Udemy	Cheap, complete deep dive	Statistical + ML (Python)	~$10–15
7	Python for Time Series Data Analysis	Udemy	Hands-on Python	Statistical (Python)	~$10–15

Best Coursera time series courses

Since a lot of people specifically search for time series courses on Coursera, let me start there, because two of the best courses on this whole list are Coursera courses, and they take opposite approaches, so between them they cover most of what you’d want.

1. Practical Time Series Analysis: Coursera (SUNY)

Best for: the best all-round starting point · Statistical approach, in R

Price ~$49/month with a 7-day free trial

This is the one I’d point most people to first. It’s from the State University of New York, and it teaches the classical statistical foundation of time series properly, trends, seasonality, autocorrelation, and the core models like ARIMA and exponential smoothing. It uses R rather than Python, which puts some people off, but the concepts are the real point and they transfer to any language.

My take: quick heads up, it uses R, not Python. I already knew a little R, so setup was fine for me, but if you’ve never touched R, that first week will feel slow. The Yule-Walker and SARIMA parts got heavy, I had to rewatch a few lectures, pause, and write the equations out by hand before they made sense. So give yourself extra time here, it’s detailed, not a weekend course.

What you’ll be able to do after: properly analyse a real time series, test for stationarity, and build and evaluate ARIMA and SARIMA models in R. So if you want to actually understand how time series works, not just run a library, this is the strongest foundation on the list.

See Practical Time Series Analysis on Coursera →

2. Sequences, Time Series and Prediction: Coursera (DeepLearning.AI)

Best for: the modern deep learning approach · Deep learning with TensorFlow

Time to Complete: ~23 hours

Price: ~$49/month

This is the other Coursera course worth your time, and it’s the opposite approach. It’s part of Andrew Ng’s DeepLearning.AI TensorFlow specialization, and it teaches time series forecasting with neural networks, RNNs and 1D ConvNets, ending in a real sunspot prediction project.

My take: this is my favorite for the deep learning side. It’s by DeepLearning.AI and you can feel the quality. I already knew Python, so I could focus on the ideas instead of fighting the code. Building the RNN for time series was the fun part, and when I ran it on real-world data at the end and the prediction actually followed the pattern, that felt so good. It’s only about 23 hours, so you can finish it in a couple of weeks.

What you’ll be able to do after: prepare time series data for neural networks and build RNN and 1D-ConvNet forecasting models in TensorFlow, ending with a real sunspot prediction project. One honest note, it assumes some prior TensorFlow and deep learning knowledge, so it’s not a day-one beginner course. If neural networks are new to you, my deep learning roadmap will get you ready for this first.

See Sequences, Time Series and Prediction →

3. Analyzing Time Series and Sequential Data Specialization: Coursera

Best for: large-scale forecasting, taught with SAS · Statistical (SAS)

Time to Complete: ~7 months

Price: ~$49/month

Quick but important heads up before you enrol: this is a SAS specialization. It uses SAS tools and PROC TSMODEL, not Python or R. So know that going in.

My take: I took it because I wanted to understand large-scale forecasting, and this course does that part really well. Seven months is a lot though, I treated it like a slow side project, not a sprint. The Bayesian time series part was new for me and I really enjoyed it. But if you don’t have a stats background, this will be tough, so build your basics first.

What you’ll be able to do after: handle large-scale, automated forecasting workflows in SAS, including Bayesian time series methods. So choose this only if you specifically want the SAS enterprise-forecasting skillset and have the stats foundation for it.

See the Time Series specialization on Coursera →

Best free time series course

4. Time Series Forecasting: Udacity (Free)

Best for: a completely free start · Statistical approach

Time to Complete: ~3 weeks

This is a genuinely free Udacity course, and it’s a solid place to start if you don’t want to pay yet. Across four lessons it covers the fundamentals, time series components (trend, seasonality, cyclical patterns), ETS models and decomposition, Holt-Winters, and ARIMA and seasonal ARIMA models, with quizzes throughout to test yourself.

My take: this was the first course I picked when I started with time series, because it’s free and I didn’t wanna spend money before I knew if I even liked the topic. The four lessons are short, I finished the fundamentals part in one sitting, and the quizzes after each lesson really helped, I’d forget a concept, get it wrong in the quiz, and then it would finally stick. When I reached the ARIMA lessons I slowed down a lot, that part is not easy the first time, so don’t rush it.

What you’ll be able to do after: decompose a time series into trend and seasonality, and build basic forecasts with ETS, Holt-Winters, and ARIMA models. So if you want the classical forecasting toolkit for free before committing money anywhere, start here. It’s aimed at the intermediate level, so a little prior stats helps, but it’s the best no-cost option on the list.

See the free Time Series Forecasting course →

5. Machine Learning for Trading: Udacity

Best for: time series applied to finance and trading · ML approach

Price: Free to audit

If your interest in time series is specifically about markets and trading, this Udacity course applies machine learning and time series to financial data.

My take: this one is long, four months, and I’m being honest, I did not finish it in one go, I kept coming back to it. What I loved was the Bollinger Bands and daily returns part, I ran it on real stock data right after the lesson, and seeing my own chart move was the moment it clicked. The interview with Tammer Kamel at the end is worth your time too. But you need real coding skills before you start, if you’re new to Python, do a smaller course first.

What you’ll be able to do after: work with real financial time series, compute indicators like Bollinger Bands and daily returns, and apply ML to trading data. So take this one if finance is your motivation, rather than a general time series course.

See Machine Learning for Trading →

Best Udemy time series courses

A lot of people also search specifically for time series courses on Udemy, and the appeal is obvious, you buy once, own it forever, and prices drop to around $10 to $15 in the frequent sales. So here are the two worth grabbing.

6. Time Series Analysis, Forecasting, and Machine Learning: Udemy

Best for: a cheap, complete deep dive · Statistical + ML in Python

Price: ~$10–15 on sale

This is the most complete Udemy option, and it covers a lot for the price, classical methods like ARIMA, plus machine learning and deep learning approaches, all in Python.

My take: this one is packed. It goes from the basics all the way to GARCH, AWS Forecast, and Facebook Prophet. Prophet was the part I kept coming back to in my own projects, because it’s fast and you get a decent forecast without a lot of setup. The ARIMA and stationarity sections are solid too. You do need some Python before this, but if you have that, it’s one of the most complete courses on the whole list.

What you’ll be able to do after: build forecasts across the whole spectrum, ARIMA, GARCH, Facebook Prophet, and AWS Forecast, in Python. So if you want one paid course that covers everything without a subscription, this is strong value. Just wait for a sale, Udemy runs them constantly, and never pay full sticker price.

See Time Series Analysis, Forecasting and ML on Udemy →

7. Python for Time Series Data Analysis: Udemy

Best for: hands-on Python-first learning · Statistical in Python

Price:~$10–15 on sale

If you specifically want to learn time series in Python with a hands-on, code-along style, this Udemy course focuses exactly there.

My take: if you want something short and in Python, this is the one I’d point you to, it’s only 15.5 hours. The Pandas time series part was so useful, DateTime index, resampling, time shifting, I use all of these in my real work now. It’s not the deepest course here, but it gets you doing time series in Python fast, and honestly, sometimes that’s exactly what you need to just get started.

What you’ll be able to do after: handle time series in Pandas confidently, DateTime indexing, resampling, time shifting, and build practical forecasts in Python. So pick this one if Python is your language and you want practical skills fast and cheap.

See Python for Time Series Data Analysis →

Coursera vs Udemy for time series: which should you pick?

Since these are the two platforms people compare most for time series, let me make the choice simple. Coursera is better if you want structured, university or DeepLearning.AI-backed courses with a recognized certificate, and you’re okay with a subscription (around $49 a month, with a 7-day free trial). Udemy is better if you want to own a course forever for around $10 to $15 and learn at your own pace with no subscription. So for a recognized credential and structured depth, Coursera; for cheap, permanent, practical courses, Udemy. Many people do both, a Coursera course for the foundation and certificate, a Udemy one as a cheap Python reference.

The order to learn time series (a simple path)

So time series has a lot of methods, and grabbing them randomly is confusing. So let me lay out the order I’d learn them in, and it’s roughly the order I did.

Step 1: The fundamentals. Trend, seasonality, decomposition, stationarity. Understand what a time series is made of before you model it. The free Udacity course covers this well.

Step 2: Classical statistical models. ETS, Holt-Winters, and especially ARIMA and SARIMA. This is the backbone of time series, and it’s what most forecasting still runs on. Practical Time Series Analysis or the Udemy complete course teach this.

Step 3: Practical tools in your language. Get fluent handling time series in Python (Pandas datetime, resampling) or R. This is where you go from theory to actually doing it. The Python-focused Udemy course is built for this.

Step 4: Modern ML and deep learning methods. Facebook Prophet for quick forecasts, then neural networks (RNNs, LSTMs) for the deep learning approach. DeepLearning.AI’s course is the best for this step.

Step 5: Specialise if you want. Finance and trading, or large-scale enterprise forecasting with SAS, after you have the foundation.

So start with the fundamentals and classical models, get hands-on in your language, then add the modern ML methods. Don’t jump straight to LSTMs without understanding ARIMA first, the classical foundation is what makes the modern stuff clear.

Which time series course should you choose?

Let me match it to you simply. If you’re starting out and want the best foundation, take Practical Time Series Analysis on Coursera. If you want it free first, the Udacity Time Series Forecasting course. If you already know deep learning and want the modern approach, DeepLearning.AI’s Sequences, Time Series and Prediction. If you want cheap and complete in Python, the Udemy Time Series Analysis course. And if your goal is trading, Machine Learning for Trading.

One honest thing across all of them, no course makes you good at time series by itself. You get good by forecasting real data, your own or public datasets, and seeing where your models fail. So whichever you pick, build a small forecasting project alongside it. That’s what turns course knowledge into a skill you can actually use, and into a portfolio piece.

FAQ

And that’s all…So, these are the 7 Best Time Series Courses Online. Now, it’s time to wrap up.

Conclusion

So those are the seven best time series courses online in 2026. For the best foundation, take Practical Time Series Analysis on Coursera. For the deep learning approach, DeepLearning.AI’s Sequences, Time Series and Prediction. For a free start, the Udacity Time Series Forecasting course. And for cheap, complete Python courses you own forever, the Udemy options in a sale.

So pick the one that matches where you are and how you like to learn, then build a real forecasting project alongside it. That’s how time series goes from something you studied to something you can actually do.

I hope these 7 Best Time Series Courses Online will help you to learn Time Series in detail. My aim is to provide you with the best resources for Learning. If you have any doubts or questions, feel free to ask me in the comment section.

Tell me in the comment section, which course you like.

All the Best!

Happy Learning!

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