Practical Python for Time Series Analysis & Modelling

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Free Download Practical Python for Time Series Analysis & Modelling
Published 8/2024
Created by Jesús López
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 36 Lectures ( 2h 26m ) | Size: 1.3 GB

A course to learn how to handle time series through practical cases, especially in the energy sector.
What you'll learn:
Handling time series al dente
Visually analyse a series with a variety of charts
Model the future with statistical and Deep Learning algorithms
Decompose and differentiate the elements that make up the time series
Requirements:
We'll explain everything step by step, starting from blank notebooks. Therefore, any beginner can take the course. However, if you're already familiar with Python or data analysis, you'll progress more comfortably.
Description:
### Course DescriptionWould you like to master the analysis and modeling of time series using Python? This course is perfect for you. Through practical cases from the energy sector, you will learn how to handle temporal data, identify patterns, and make accurate predictions.In this course, you will acquire essential skills to:- **Preprocess and visualize temporal data**: Learn how to clean and prepare your data for detailed analysis, and create visualizations that make it easier to identify trends and patterns.- **Decompose time series**: Understand how to separate trend, seasonality, and noise components in both additive and multiplicative models.- **Ensure stationarity and manage seasonality**: Discover key techniques to transform your data and make modeling easier.- **Apply statistical and deep learning models**: Develop robust predictive models using traditional statistical methods and advanced neural network techniques.- **Evaluate and improve your models**: Use error metrics and data scaling techniques to enhance the accuracy of your predictions.### Who is this course for?- **Data analysts and scientists**: Who want to deepen their understanding of time series analysis and apply this knowledge in real-world projects.- **Energy sector professionals**: Who need to optimize the management and prediction of resources through the use of historical data and predictive models.- **Students and data analysis enthusiasts**: Who wish to specialize in one of the most in-demand areas and learn practical techniques applicable across multiple industries.### MethodologyThe course is designed to be highly practical. Through real-world examples and interactive exercises, you'll be able to immediately apply what you learn. Each module is structured to provide both fundamental theory and practical application, ensuring a comprehensive and applicable understanding of time series concepts.
Who this course is for:
Beginners who want to learn while solving exercises based on real-world practical cases.
Professionals who work with time series in Excel and want to transition to Python to better automate their processes.
Energy sector professionals who need to interpret statistics and mathematical models for time series.
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