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Python for Time Series Analysis and Forecasting

Work with time series and time related data in Python - Forecasting, Time Series Analysis, Predictive Analytics
4.2
4.2/5
(395 reviews)
2,296 students
Created by

8.3

CourseMarks Score®

6.6

Freshness

8.4

Feedback

9.4

Content

Platform: Udemy
Video: 5h 11m
Language: English
Next start: On Demand

Top Time Series Analysis courses:

Detailed Analysis

CourseMarks Score®

8.3 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

6.6 / 10
This course was last updated on 3/2019.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.4 / 10
We analyzed factors such as the rating (4.2/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.4 / 10
Video Score: 8.3 / 10
The course includes 5h 11m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 7 hours 03 minutes of 14 Time Series Analysis courses on Udemy.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

2 articles.
6 resources.
0 exercise.
0 test.

Table of contents

Description

Use Python to Understand the Now and Predict the Future!
Time series analysis and forecasting is one of the key fields in statistical programming. It allows you to
•see patterns in time series data
•model this data
•finally make forecasts based on those models
•and of of this you can now do with the help of Python
Due to modern technology the amount of available data grows substantially from day to day. Successful companies know that. They also know that decisions based on data collected in the past, and modeled for the future, can make a huge difference. Proper understanding and training in time series analysis and forecasting will give you the power to understand and create those models. This can make you an invaluable asset for your company/institution and will boost your career!
•What will you learn in this course and how is it structured?
First of all we will discuss the general idea behind time series analysis and forecasting. It is important to know when to use these tools and what they actually do.
After that you will learn about statistical methods used for time series. You will hear about autocorrelation, stationarity and unit root tests.   You will also learn how to read a time series chart. This is a crucial skill because things like mean, variance, trend or seasonality are a determining factor for model selection.
We will also create our own time series charts including smoothers and trend lines.
Then you will see how different models work, how they are set up in Python and how you can use them for forecasting and predictive analytics. Models taught are: ARIMA, exponential smoothing, seasonal decomposition and simple models acting as benchmarks. Of course all of this is accompanied by homework assignments.
•Where are those methods applied?
In nearly any field you will see those methods applied. Especially econometrics and finance love time series analysis. For example stock data has a time component which makes this sort of data a prime target for forecasting techniques. But of course also in academia, medicine, business or marketing  techniques taught in this course are applied.
•Is it hard to understand and learn those methods?
Unfortunately learning material on Time Series Analysis Programming in Python is quite technical and needs tons of prior knowledge to be understood.
With this course it is the goal to make modeling and forecasting as intuitive and simple as possible for you.
While you need some knowledge in maths and Python, the course is meant for people without a major in a quantitative field. Basically anybody dealing with time data on a regular basis can benefit from this course.
•How do I prepare best to benefit from this course?
It depends on your prior knowledge. But as a rule of thumb you should know how to handle standard tasks in Python.

You will learn

✓ use Python to perform calculations with time and date based data
✓ create models for time series data
✓ use models for forecasting
✓ identify which models are suitable for a given dataset
✓ visualize time series data
✓ create ARIMA and exponential smoothing models
✓ know how to interpret given models
✓ understand time series statistics such as autocorrelation or stationarity
✓ use machine learning and deep learning for time series
✓ know the alternatives to qualitative methods
✓ know how to read a time series plot and understand it (trend, seasonality, constant mean and variance)

Requirements

• computer with Python and Anaconda ready to use
• basic Python and Anaconda knowledge (installing packages, Anaconda usage, Python basics)
• no statistics or time series knowledge is required before the course, you will learn all the relevant things!
• time and patience to reproduce the examples and to solve the exercises

This course is for

• data analysts working with time series data (which is essentially any data analyst at some point in the career)
• people using Python
• this course is for people working in various fields like (and not limited to): academia, marketing, business, econometrics, finance, medicine, engineering and science
• generally if you have time series data on your table and you do not know what to do with it and Python, take this course!

How much does the Python for Time Series Analysis and Forecasting course cost? Is it worth it?

The course costs $12.99. And currently there is a 85% discount on the original price of the course, which was $84.99. So you save $72 if you enroll the course now.
The average price is $12.6 of 14 Time Series Analysis courses on Udemy.

Does the Python for Time Series Analysis and Forecasting course have a money back guarantee or refund policy?

YES, Python for Time Series Analysis and Forecasting has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Python for Time Series Analysis and Forecasting course, but there is a $72 discount from the original price ($84.99). So the current price is just $12.99.

Who is the instructor? Is R-Tutorials Training a SCAM or a TRUSTED instructor?

R-Tutorials Training has created 24 courses that got 30,289 reviews which are generally positive. R-Tutorials Training has taught 245,845 students and received a 4.5 average review out of 30,289 reviews. Depending on the information available, R-Tutorials Training is a TRUSTED instructor.
Data Science Education
  R-Tutorials is your provider of choice when it comes to analytics training courses! Try it out – our 100,000+ students love it.          We focus on Data Science tutorials. Offering several R courses for every skill level, we are among Udemy’s top R training provider. On top of that courses on Tableau, Excel and a Data Science career guide are available.        All of our courses contain exercises to give you the opportunity to try out the material on your own. You will also get downloadable script pdfs to recap the lessons.          The courses are taught by our main instructor Martin – trained biostatistician and enthusiastic data scientist / R user.          Should you have any questions, you are invited to check out our website, you can open a discussion in the course or you can simply drop us a pm.          We are here to help you boost your career with analytics training – Just learn and enjoy.  Show moreShow less

8.3

CourseMarks Score®

6.6

Freshness

8.4

Feedback

9.4

Content

Platform: Udemy
Video: 5h 11m
Language: English
Next start: On Demand

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