Master Time Series Analysis and Forecasting with Python 2025
- Descrição
- Currículo
- FAQ
- Revisões
Updates December 2024:
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Amazon AutoGluon launched
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Library requirements.txt file for all sections added
Updates October 2024:
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Amazon Chronos launched
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N-BEATS launched
Updates September 2024:
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TFT and TFT Capstone Project added
Updates August 2024:
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Course remade 100%
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Silverkite, LSTM and Projects added
Welcome to the most exciting online course about Forecasting Models in Python. 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?
Master the Intuition Behind Forecasting Models
No need to get bogged down in complex math. This course emphasizes understanding the why behind each model. We simplify the concepts with clear explanations, intuitive visuals, and real-world examples—focusing on what really matters so you can apply these techniques confidently.
Comprehensive Coverage of Cutting-Edge Techniques
You’ll dive deep into the most advanced and sought-after time series forecasting methods that are crucial in today’s data-driven world:
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Exponential Smoothing & Holt-Winters: Perfect for handling trends and seasonality in your data.
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Advanced ARIMA Models (SARIMA & SARIMAX): Master these foundational models and learn how to incorporate external variables for enhanced forecasts.
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Facebook Prophet: Make robust, high-accuracy forecasts with minimal data preparation.
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Temporal Fusion Transformers (TFT): Leverage state-of-the-art deep learning techniques to forecast multiple time series with high accuracy.
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LinkedIn Silverkite: Understand and apply this powerful, flexible model for accurate predictions in various contexts.
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N-BEATS: Utilize cutting-edge neural network models for handling a variety of time series forecasting challenges.
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GenAI with Amazon Chronos: Explore how generative AI is revolutionizing forecasting with models like Amazon Chronos.
Code Python Together, Line by Line
We’ll code together, ensuring you understand each step of the process. From data preparation to model implementation, you’ll learn how to write and refine every line of Python code needed to master these forecasting techniques.
Practice, Practice, Practice
Each lesson includes hands-on challenges and case studies, allowing you to immediately apply what you’ve learned. You’ll work with real datasets, solving real-world problems, and solidifying your skills through practical application.
Are You Ready to Predict the Future?
Did I spike your interest? Join me and learn how to predict the future!
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1Time Series Analysis and Forecasting with PythonVídeo Aula
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2Course IntroductionVídeo Aula
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3[ACTION] Download the Course MaterialsTexto
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4Diogo's Introduction and BackgroundVídeo Aula
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5Unlimited Updates and Enhancements 2025Vídeo Aula
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6Submit Your Update and Enhancement Requests HereTexto
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8Game Plan for Introduction to Time Series ForecastingVídeo Aula
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9What is Time Series Data?Vídeo Aula
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10Python - Libraries and DataVídeo Aula
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11Python - Time Series IndexVídeo Aula
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12Python - Exploratory Data AnalysisVídeo Aula
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13Python - Data VisualizationVídeo Aula
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14Python - Data ManipulationVídeo Aula
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15Seasonal DecompositionVídeo Aula
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16Python - Seasonal PlotsVídeo Aula
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17Python - Seasonal DecompositionVídeo Aula
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18Auto-CorrelationVídeo Aula
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19Python - Auto-correlationVídeo Aula
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20Partial Auto-CorrelationVídeo Aula
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21Python - Partial Auto-CorrelationVídeo Aula
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22Python - Building a Useful Function ScriptVídeo Aula
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23Can you predict stock prices?Vídeo Aula
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24What did we learn in this section?Vídeo Aula
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25CASE STUDY: Forecasting Gone WrongVídeo Aula
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26Will you help me?Vídeo Aula
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27Your Feedback is ValuableTexto
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28Game Plan For Exponential Smoothing and Holt-WintersVídeo Aula
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29CASE STUDY BRIEFING: Customer ComplaintsVídeo Aula
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30Python - Set UpVídeo Aula
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31Python - Data ProcessingVídeo Aula
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32Python - Exploratory Data AnalysisVídeo Aula
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33Training and Test Set in Time SeriesVídeo Aula
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34Python - Training and Test SetVídeo Aula
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35Simple Exponential SmoothingVídeo Aula
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36Python - Simple Exponential SmoothingVídeo Aula
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37Double Exponential SmoothingVídeo Aula
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38Python - Double Exponential SmoothingVídeo Aula
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39Triple Exponential Smoothing aka Holt-WintersVídeo Aula
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40Python - Triple Exponential Smoothing aka Holt-WintersVídeo Aula
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41Measuring Errors for Time Series ForecastingVídeo Aula
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42Python - MAE, RMSE, MAPEVídeo Aula
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43Python - Predicting The FutureVídeo Aula
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44Python - Daily DataVídeo Aula
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45Python - Working on the Useful Code ScriptVídeo Aula
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46Holt-Winter Pros and ConsVídeo Aula
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50Game Plan for ARIMA, SARIMA and SARIMAXVídeo Aula
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51CASE STUDY BRIEFING: Predicting Daily RevenuesVídeo Aula
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52Python - Setting UpVídeo Aula
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53ARIMAVídeo Aula
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54Auto-RegressiveVídeo Aula
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55IntegratedVídeo Aula
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56Python - Stationarity with ChatGPTVídeo Aula
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57Moving AverageVídeo Aula
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58Python - ARIMAVídeo Aula
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59AIC and BICVídeo Aula
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60SARIMAVídeo Aula
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61Python - SARIMAVídeo Aula
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62SARIMAXVídeo Aula
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63Python - SARIMAXVídeo Aula
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64Cross-Validation for Time SeriesVídeo Aula
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65Python - Cross-ValidationVídeo Aula
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66Parameter TuningVídeo Aula
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67Python - Setting the ParametersVídeo Aula
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68Python - Parameter TuningVídeo Aula
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69Python - Parameter Tuning ResultsVídeo Aula
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70Python - Predicting The Future Set UpVídeo Aula
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71Python - Predicting The FutureVídeo Aula
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72SARIMAX Pros and ConsVídeo Aula
