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Keep shoppingComplete Time Series Forecasting Bootcamp in Python (2025)
219 students
Complete Time Series Forecasting Bootcamp in Python (2025)
Master time series forecasting from statistical to state-of-the-art deep learning models in 100% Python code
Created byMarco Peixeiro
Last updated 1/2025
English
What you'll learn
- The basics of time series forecasting using baseline models
- Apply statistical models like ARIMA, ETS, TBATS and more
- Apply deep learning architectures for time series forecasting
- Use state-of-the-art deep learning models like NHITS, TSMixer, iTransformer, TimeGPT, and more!
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Course content
9 sections • 57 lectures • 8h 40m total length
Requirements
- Basic knowledge of Python
Description
Master Time Series Forecasting: From Fundamentals to Deep Learning
Unlock the power of predictive analytics in this comprehensive 12-hour course designed specifically for aspiring data scientists. Whether you're looking to forecast market trends, optimize supply chains, or predict weather patterns, this course will equip you with the essential skills to tackle real-world forecasting challenges.
What You'll Learn
Transform from a beginner to a confident practitioner through our carefully structured curriculum. Starting with fundamental statistical models, you'll progress to implementing cutting-edge deep learning architectures. Along the way, you'll master:
Classical forecasting methods (ARIMA, SARIMA, SARIMAX)
Advanced techniques like exponential smoothing, TBATS, and the Theta model
Deep learning architectures for time series
Facebook's Prophet framework
Why This Course Stands Out
14+ hands-on projects that reinforce your learning
100% Python-based curriculum with complete code implementations
Real-world applications across finance, economics, retail, and supply chain
Progressive learning path from basics to advanced concepts
Perfect For You If...
You're new to time series forecasting but have basic Python programming skills. No prior forecasting experience needed – we'll guide you through every step, from understanding the fundamentals to implementing advanced predictive models.
Course Structure
The curriculum flows naturally from foundational concepts to advanced applications:
Core statistical methods and their practical implementation
Multivariate forecasting techniques for complex datasets
Deep learning approaches built from the ground up
Modern frameworks and state-of-the-art architectures
About Your Instructor
Learn from an industry expert at the forefront of time series innovation. I am a contributor at Nixtla, a leader in open-source forecasting technology, and an active developer of NeuralForecast, the Python package renowned for its lightning-fast deep learning implementations. This isn't just theoretical knowledge – it's practical insight from someone who shapes the tools that industry leaders use today.
By the end of this course, you'll have the skills and confidence to tackle diverse forecasting challenges across any industry. Join us to master one of the most valuable skills in data science, backed by extensive hands-on practice and real-world applications.
Ready to predict the future? Enroll now and transform your data science journey.
Who this course is for:
- Beginners eager to learn about time series forecasting
- Practitioners looking to perfect their forecasting skills
- Anyone serious about mastering time series forecasting using state-of-the-art models