Udemy – Complete Time Series Forecasting Bootcamp in Python 2025-1

Udemy – Complete Time Series Forecasting Bootcamp in Python 2025-1 Downloadly IRSpace

Apr 18, 2025 - 18:24 Updated: Aug 17, 2025 - 18:23

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Udemy – Complete Time Series Forecasting Bootcamp in Python 2025-1

Complete Time Series Forecasting Bootcamp in Python is a course on analyzing and forecasting time series data using Python, published by Udemy Online Academy. Starting with the basics of time series analysis, the bootcamp covers fundamental concepts such as stationarity, trend, seasonality, and autocorrelation. It then explores various statistical and machine learning models used for forecasting, including ARIMA, SARIMA, Prophet, and LSTM (Long Short-Term Memory) networks. The course provides hands-on experience by walking participants through real-world datasets and enabling them to apply the methods learned.

Unleash the power of predictive analytics in this comprehensive 12-hour course designed specifically for aspiring data scientists. Whether you’re looking to predict market trends, optimize supply chains, or predict weather patterns, this course will equip you with the essential skills to tackle real-world forecasting challenges. Individuals will also explore model evaluation techniques, feature engineering, and performance optimization for accurate forecasting. By the end of the course, learners will be able to build, tune, and deploy robust time series forecasting models.

What you will learn in Complete Time Series Forecasting Bootcamp in Python:

Fundamentals of Time Series Forecasting Using Basic Models
Use statistical models like ARIMA, ETS, TBATS, etc
Use deep learning architectures for time series forecasting
Use the most advanced deep learning models like NHITS, TSMixer, iTransformer, TimeGPT, and more!
And…

Course specifications

Publisher: Udemy
Instructors: Marco Peixeiro
Language: English
Level: Introductory to Advanced
Number of Lessons: 85
Duration: 11 hours and 56 minutes