Udemy – Master Time Series Analysis and Forecasting with Python 2025 2024-11

Published on: 2024-11-26 12:02:05

Categories: 28

Descriptions

Master Time Series Analysis and Forecasting with Python 2024, 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. 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. 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. 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.

What you’ll learn

Understand the fundamental principles of time series data and its significance in forecasting across various industries.
Differentiate between various time series forecasting models such as Exponential Smoothing, ARIMA, and Prophet, identifying when to use each model.
Apply Exponential Smoothing and Holt-Winters methods to seasonal and trend-based time series data to create accurate forecasts.
Implement SARIMA and SARIMAX models in Python, incorporating external variables to enhance the predictive power of your forecasts.
Develop time series models using advanced techniques such as Temporal Fusion Transformers (TFT) and N-BEATS to handle complex datasets.
Optimize forecasting models by tuning parameters and using ensemble methods to improve accuracy and reliability.
Evaluate the performance of different forecasting models using metrics such as MAE, RMSE, and MAPE, ensuring the robustness of your predictions.
Code Python scripts to automate the entire time series forecasting process, from data preprocessing to model deployment.
Implement deep learning models such as RNN and LSTM to accurately forecast complex time series data, capturing long-term dependencies.
Develop and optimize advanced forecasting solutions using Generative AI techniques like Amazon Chronos, incorporating state-of-the-art methods.

Who this course is for

Business analysts looking to improve their forecasting skills and techniques.
Data scientists interested in applying time series analysis and forecasting to business problems.
Marketing professionals looking to forecast future demand for products or services.
Financial analysts seeking to forecast future trends and performance for businesses.
Operations managers looking to improve demand planning and forecasting for their organization.

Specificatoin of Master Time Series Analysis and Forecasting with Python 2024

Publisher : Udemy
Teacher : Diogo Alves de Resende
Language : English
Level : Beginner
Number of Course : 452
Duration : 42 hours and 53 minutes

Content

Master Time Series Analysis and Forecasting with Python 2025

Requirements

Basic Statistics: Linear regression, p-value

Pictures

Master Time Series Analysis and Forecasting with Python 2025

Sample Clip

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Installation Guide

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Subtitle : English

Quality: 1080p

The 2024/11 version has increased by 105 lessons and a duration of 34 hours and 42 minutes compared to 2021/6. The course quality has also increased from 720p to 1080p.