Applied Time Series Analysis and Forecasting with R Projects

Applied Time Series Analysis and Forecasting with R Projects, available at $64.99, has an average rating of 4.58, with 34 lectures, based on 792 reviews, and has 5330 subscribers.

You will learn about Perform standard time series analysis tasks Get ARIMA and exponential smoothing models in R Do forecasting in R Work with irregularly spaced time series Model time series with trend and seasonality Scrape stock data from yahoo finance Import different types of time series data Use automatic model selection in R Select the best packages for time series analysis in R This course is ideal for individuals who are Data scientists, economists and all sorts of professionals working with time series datasets or Entrepreneurs and marketing experts interested in finding patterns in time series data or Students required to perform time series analysis It is particularly useful for Data scientists, economists and all sorts of professionals working with time series datasets or Entrepreneurs and marketing experts interested in finding patterns in time series data or Students required to perform time series analysis.

Enroll now: Applied Time Series Analysis and Forecasting with R Projects

Summary

Title: Applied Time Series Analysis and Forecasting with R Projects

Price: $64.99

Average Rating: 4.58

Number of Lectures: 34

Number of Published Lectures: 34

Number of Curriculum Items: 34

Number of Published Curriculum Objects: 34

Original Price: $84.99

Quality Status: approved

Status: Live

What You Will Learn

Perform standard time series analysis tasks
Get ARIMA and exponential smoothing models in R
Do forecasting in R
Work with irregularly spaced time series
Model time series with trend and seasonality
Scrape stock data from yahoo finance
Import different types of time series data
Use automatic model selection in R
Select the best packages for time series analysis in R

Who Should Attend

Data scientists, economists and all sorts of professionals working with time series datasets
Entrepreneurs and marketing experts interested in finding patterns in time series data
Students required to perform time series analysis

Target Audiences

Data scientists, economists and all sorts of professionals working with time series datasets
Entrepreneurs and marketing experts interested in finding patterns in time series data
Students required to perform time series analysis

Welcome to the world of R and Time Series Analysis!

At the moment R is the leading open source software for time series analysis and forecasting. No other tool, not even python, comes close to the functions and features available in R. Things like exponential smoothing, ARIMA models, time series cross validation, missing data handling, visualizations and forecasts are easily accessible in R and its add on packages. Therefore, R is the right choice for time series analysis and this course gives you an opportunity to train and practice it.

So how is the course structured?

This is a hands on course with 3 distinct projects to solve! Each project has a main topic and a secondary topic. Both are discussed on real world data. In the first project you work with trending data, and as a secondary topic you will learn how to create standard and ggplot2 time series visualizations. The dataset for that project will be an employment rate dataset.

The second project with the German monthly inflation rates over the last 10 years shows how to model seasonal datasets. And you will also compare the models with time series cross validation.

In the third project you will connect R to yahoo finance and scrape stock data. The resulting data requires loads of pre-processing and cleaning including missing data imputation. Once we prepared the data, we will check out which weekday is the best for buying and selling the Novartis stock.

You should know some R to be able to follow along. There is for example the introduction to time series analysis and forecasting course. That course is more a step by step guide while this one is an applied and project based one. Both courses can be taken on their own, or you take a look at both and learn the subject from 2 different angles.

As always you will get the course script as a text file. Of course you get all the standard Udemy benefits like 30 days money back guarantee, lifetime access, instructor support and a certificate for your CV.

Course Curriculum

Chapter 1: Course Introduction

Lecture 1: Introduction

Lecture 2: Managing Expectations

Lecture 3: Main R Functions in Time Series Analysis

Lecture 4: Supporting Resources

Lecture 5: Course Link List

Chapter 2: Project I Trending Data: Singapur Labor Force Participation Rate

Lecture 1: Importing The Data

Lecture 2: Mission Statement

Lecture 3: Project I Script

Lecture 4: The Exponential Smoothing Family of Models

Lecture 5: The Holt Linear Trend Model

Lecture 6: The ARIMA Model

Lecture 7: Comparison Plot with 'Ggplot2'

Lecture 8: Bonus Exercise: In-Sample Forecasts vs Actual Data

Chapter 3: Project II Seasonal Data: Monthly Inflation Rates of Germany

Lecture 1: Getting Familiar with The Data

Lecture 2: Importing The Data

Lecture 3: Mission Statement

Lecture 4: Project II Script

Lecture 5: Seasonal Decomposition

Lecture 6: Seasonal ARIMA

Lecture 7: Exponential Smoothing with ETS

Lecture 8: Time Series Cross Validation

Chapter 4: Project III Irregularly Spaced Data: Analyze A Biotech Stock

Lecture 1: Mission Statement

Lecture 2: Scraping the Data From Yahoo Finance

Lecture 3: Exploring the Data

Lecture 4: Project III Script

Lecture 5: Getting a Regular Time Series

Lecture 6: Visually Analyzing the Data

Chapter 5: Project IV Neural Networks: Neural Nets and Interactive Graphs

Lecture 1: Mission Statement

Lecture 2: Getting Familiar with the Dataset

Lecture 3: Project IV Script

Lecture 4: Cleaning with tidyr

Lecture 5: Fitting the Neural Net Model

Lecture 6: Interactive Graph with Dygraphs

Lecture 7: Course Summary and Further Options

Instructors

R-Tutorials Training
Data Science Education

Rating Distribution

1 stars: 14 votes
2 stars: 14 votes
3 stars: 85 votes
4 stars: 294 votes
5 stars: 385 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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