Year of manufacture: 2026
Manufacturer: Udemy
Manufacturer’s website: https://www.udemy.com/course/forecasting-python/
Author: Diogo Alves de Resende
Duration: 37h 30m
Type of material distributed: Video lesson
Language: English, Russian, German, Italian, Korean, Portuguese, Spanish, Turkish.
- 7.93 GB
Description:
Welcome to the most exciting online course about Forecasting Models in Python.
I will show you 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 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:
Exponential Smoothing & Holt-Winters – Handle trends and seasonality with elegance.
Advanced ARIMA Models (SARIMA & SARIMAX) – Incorporate external variables for enhanced forecasts.
Facebook Prophet – Robust, high-accuracy forecasts with minimal data prep.
Temporal Fusion Transformers (TFT) – State-of-the-art deep learning for multiple time series.
LinkedIn Silverkite – Flexible, powerful forecasting across contexts.
N-BEATS – Cutting-edge neural networks for diverse forecasting challenges.
GenAI with Amazon Chronos – Discover how generative AI is revolutionizing forecasting.
Google TSMixer (NEW) – Leverage Google’s breakthrough architecture for time series.
Amazon AutoGluon (NEW) – Automate high-performance forecasting pipelines.
Intermittent Time Series (NEW) – Tackle irregular, sporadic patterns with specialized techniques.
Classification for Time Series (NEW) – Expand beyond forecasting into predictive categorization.
Code Python Together, Line by Line
We’ll code side by side, ensuring you understand every step.
From data preparation to model implementation, you’ll learn how to write and refine each line of Python code needed to master these forecasting techniques.
Practice, practice, practice
Each lesson includes hands-on challenges and case studies, from sales to demand forecasting
You’ll apply what you’ve learned to real datasets, solve real-world problems, and solidify your skills through practical application.
Content:
01-Time_Series_Analysis_and_Forecasting_with_Python
02-PART_1_TIME_SERIES_ANALYSIS
03-Python_for_Time_Series_Analysis
04-Introduction_to_Time_Series_Forecasting
05-Time_Series_Analysis_Practice
06-Exponential_Smoothing_Holt_Winters
07-HOLT_WINTERS_CAPSTONE_PROJECT_Air_miles
08-ARIMA_SARIMA_and_SARIMAX
09-PART_2_MODERN_TIME_SERIES_FORECASTING
10-Facebook_Prophet
11-CAPTONE_PROJECT_Prophet
12-Intermittent_Time_Series
13-Mid_course_Feedback
14-PART_3_DEEP_LEARNING_FOR_TIME_SERIES_FORECASTING
15-RNN_LSTM
16-LSTM_Multiple_Time_Series_Forecasting
17-Temporal_Fusion_Transformers_TFT
18-CAPSTONE_PROJECT_Multiple_Series_with_TFT
19-N_BEATS
20-PART_4_ADVANCED_CONTENT_FOR_TIME_SERIES_FORECASTING
21-GenAI_for_Time_Series_Amazon_Chronos
22-Amazon_AutoGluon
23-Google_TSMixer
24-Classification_for_Time_Series
25-End_of_Course_Feedback
26-Time_Series_Analysis_Graveyard
27-Linkedin_Silverkite
28-CAPSTONE_PROJECT_Build_an_Automated_Time_Series_Forecasting_Model
29-APPENDIX_Python_for_Data_Analysis_Course
30-Python_Essentials
31-Book_Review
32-Variable_Types_and_Operators
33-If_else_and_Conditionals
34-Python_Intermediate
35-CAPSTONE_PROJECT_Virtual_Escape_Game
36-Pandas
37-Pandas_Challenge
38-What_s_Next
Example files: present
Video format: MP4
Video: AV1 1920×1080 16:9 30fps 500 kbps
Audio: Opus 48 kHz 64 kbps 2 channels
