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A Complete Guide to Time Series Analysis & Forecasting in R

A comprehensive time series analysis and forecasting course using R
4.3
4.3/5
(10 reviews)
41 students
Created by

9.5

CourseMarks Score®

9.4

Freshness

9.1

Feedback

9.4

Content

Platform: Udemy
Video: 10h 33m
Language: English
Next start: On Demand

Top Time Series Analysis courses:

Detailed Analysis

CourseMarks Score®

9.5 / 10

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

Freshness Score

9.4 / 10
This course was last updated on 6/2021.

Course content can become outdated quite quickly.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

9.1 / 10
We analyzed factors such as the rating (4.3/5) 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: 9.2 / 10
The course includes 10h 33m 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: 9.6 / 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: 9.5 / 10

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

This course contains:

0 article.
8 resources.
0 exercise.
0 test.

Table of contents

Description

Forecasting involves making predictions. It is required in many situations: deciding whether to build another power generation plant in the next ten years requires forecasts of future demand; scheduling staff in a call center next week requires forecasts of call volumes; stocking an inventory requires forecasts of stock requirements. Forecasts can be required several years in advance (for the case of capital investments) or only a few minutes beforehand (for telecommunication routing). Whatever the circumstances or time horizons involved, forecasting is an essential aid to effective and efficient planning. This course provides an introduction to time series forecasting using R.

•No prior knowledge of R or data science is required.
•Emphasis on applications of time-series analysis and forecasting rather than theory and mathematical derivations.
•Plenty of rigorous examples and quizzes for an extensive learning experience.
•All course contents are self-explanatory.
•All R codes and data sets and provided for replication and practice.

At the completion of this course, you will be able to
•Explore and visualize time series data.
•Apply and interpret time series regression results.
•Understand various methods to forecast time series data.
•Use general forecasting tools and models for different forecasting situations.
•Utilize statistical programs to compute, visualize, and analyze time-series data in economics, business, and the social sciences.

You will learn
•Exploring and visualizing time series in R.
•Benchmark methods of time series forecasting.
•Time series forecasting forecast accuracy.
•Linear regression models.
•Exponential smoothing.
•Stationarity, ADF, KPSS, differencing, etc.
•ARIMA, SARIMA, and ARIMAX (dynamic regression) models.
•Other forecasting models.

You will learn

✓ Explore and visualize time series data.
✓ Apply and interpret time series regression results.
✓ Understand various methods to forecast time series data.
✓ Use general forecasting tools and models for different forecasting situations.
✓ Utilize statistical program to compute, visualize, and analyze time series data in economics, business, and the social sciences.
✓ Use benchmark methods of time series forecasting.
✓ Use methods for checking whether a forecasting method has adequately utilized the available information.
✓ Forecast using exponential smoothing methods.
✓ Stationarity, ADF, KPSS, differencing, etc.
✓ Forecast using ARIMA, SARIMA, and ARIMAX.
✓ Learn through plenty of rigorous examples and quizzes.

Requirements

• A computer with R and Rstudio.
• Basic knowledge of statistical terms, e.g., mean, median, mode, standard deviation, variance, etc.
• Preferably, some knowledge of R programming.

This course is for

• This course is for you if you are interested in solving economics, business, and the social sciences problems using data.
• This course is for you if you are interested in learning problem solving using a statistical program.
• This course is for you if you have basic knowledge of R language or are willing to learn the basic of R.

How much does the A Complete Guide to Time Series Analysis & Forecasting in R course cost? Is it worth it?

The course costs $14.99. And currently there is a 25% discount on the original price of the course, which was $19.99. So you save $5 if you enroll the course now.
The average price is $12.6 of 14 Time Series Analysis courses on Udemy.

Does the A Complete Guide to Time Series Analysis & Forecasting in R course have a money back guarantee or refund policy?

YES, A Complete Guide to Time Series Analysis & Forecasting in R 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 A Complete Guide to Time Series Analysis & Forecasting in R course, but there is a $5 discount from the original price ($19.99). So the current price is just $14.99.

Who is the instructor? Is Dr. Imran Arif a SCAM or a TRUSTED instructor?

Dr. Imran Arif has created 1 courses that got 10 reviews which are generally positive. Dr. Imran Arif has taught 41 students and received a 4.3 average review out of 10 reviews. Depending on the information available, Dr. Imran Arif is a TRUSTED instructor.
Assistant Professor of Economics
Welcome to Time Series Analysis and Forecasting!




I am Assistant Professor of Economics at Appalachian State University. I am very passionate about data science and modeling. I have been teaching Time Series Analysis and Forecasting in the MS Applied Data Analytics program for several years. This course is based on some of the most innovative economics and machine learning models.

9.5

CourseMarks Score®

9.4

Freshness

9.1

Feedback

9.4

Content

Platform: Udemy
Video: 10h 33m
Language: English
Next start: On Demand

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