Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
9 Hour(s) 6 Minute(s)
Language
English
Taught by
Diogo Alves de Resende
Rating
Course Overview
Time Series Analysis for Data Science & Analytics in R programming. Demand Planning & Forecasting. Prophet, ARIMA & more
How many times have you wanted to predict the future?
Welcome to the most exciting online course about Forecasting Models and Time Series in R. I will show everything you need to know to understand the now and predict the future.
Forecasting is always sexy - knowing what will happen usually drops jaws and earns admiration. On top, it is fundamental in the business world. Companies always provide Revenue growth and EBIT estimates, which are based on forecasts. Who is doing them? Well, that could be you!
WHY SHOULD YOU ENROLL IN THIS COURSE?
1 | YOU WILL LEARN THE INTUITION BEHIND THE TIME SERIES MODELS WITHOUT FOCUSING TOO MUCH ON THE MATH
It is crucial that you know why a model makes sense and the underlying assumptions behind it. I will explain to you each model using words, graphs, and metaphors, leaving math and the Greek alphabet to a minimum.
2 | THOROUGH COURSE STRUCTURE OF MOST IMPACTFUL TIME SERIES FORECASTING MODEL TECHNIQUES
The techniques in this course are the ones I believe will be most impactful, up-to-date, and sought after:
Holt-Winters
Sarimax
Facebook Prophet
Neural Networks AutoRegression
Ensemble approach
3 | WE CODE TOGETHER LINE BY LINE
I will guide you through every step of the way in your journey to master time series and forecasting models. I will also explain all parameters and functions that you need to use, step by step.
4 | YOU APPLY WHAT YOU ARE LEARNING IMMEDIATELY
At the end of each section regarding forecasting techniques, you are shown an exercise to apply what you learn immediately. If you do not manage? Don't worry! We also code together line by line the solutions. The challenges range from predicting the interest in Churrasco (Brazilian BBQ) to the Wikipedia visitors of Udemy.
Did I spike your interest? Join me and learn how to predict the future!
Course Content
- 13 section(s)
- 147 lecture(s)
- Section 1 Introduction
- Section 2 Introduction to Forecasting
- Section 3 Seasonal Decomposition
- Section 4 Exponential Smoothing and Holt-Winters
- Section 5 Forecasting Product
- Section 6 ARIMA, SARIMA, and SARIMAX
- Section 7 Facebook Prophet
- Section 8 Facebook Prophet - Parameter Tuning
- Section 9 Neural Networks AutoRegression - Deep Learning
- Section 10 Neural Networks AutoRegression and Deep Learning - Parameter Tuning
- Section 11 Ensemble
- Section 12 EXTRA CONTENT: Time Series Visualization
- Section 13 What's Next?
What You’ll Learn
- Gain a comprehensive understanding of time series analysis and forecasting models through hands-on practice and real-world applications, Implement forecasting models and time series analysis in a business environment to improve performance and efficiency., Understand and apply various forecasting models, including Prophet and ARIMA, to make informed business decisions., Apply data science and analytics principles to real-world business scenarios through hands-on practice in R., Develop proficiency in using R programming for time series analysis in business settings., Improve demand planning and forecasting abilities by utilizing time series analysis techniques., Learn to analyze and interpret time series data to make predictions about future trends and patterns., Utilize R programming to create visualizations and data visualizations to better understand time series data., Understand the importance of forecasting models in business operations and decision-making., Learn to identify and diagnose common problems and limitations in time series analysis.
Skills covered in this course
Reviews
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SShaik Karishma
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JJieping Ding
m increased from 32 rows to 2665 rows, hard to understand
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MMashkur Zafar
good untill now
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JJanaka Chandana Wijayawickrama
good so far
