LinkedIn – AI-Powered Time Series Forecasting with Python 2024-8

AI-Powered Time Series Forecasting with Python course. This course teaches you how to make time series forecasts using Python and artificial intelligence. You will learn how to transform forecasting processes from static and classical to dynamic and real-world applications. You will also learn tools and approaches that you can use in other AI and machine learning tasks.

This course will help you gain an in-depth understanding of time series forecasting and be able to use this knowledge to improve your business decisions. You will get to know the basic concepts of time series, different forecasting models and how to implement them in Python. This course will help you make more accurate predictions of the future using Python and artificial intelligence. You will learn how to build, train and use predictive models to analyze a variety of data. This course is suitable for people who want to use their data to improve their business decisions.

What you will learn

• Batch Systems: Learn how to build batch features, train a model to make predictions, and make predictions with the model.
• Near-Real-Time Systems: Understanding the Requirements for Near-Real-Time Prediction Systems, Feature Recalculation and Online Forecasting.
• Real-time systems: Familiarity with the requirements of real-time forecasting systems, working with streaming data sets and online forecasting.

This course is suitable for people who

• They are interested in machine learning and artificial intelligence.
• They want to use their data to predict the future.
• Looking to improve their business decisions.
• They want to learn about cloud development tools like GitHub Codespaces.
• They have knowledge of Python programming.

Course specifications AI-Powered Time Series Forecasting with Python

• Publisher: LinkedIn
• Lecturer: Tobias Zwingmann
• Training level: beginner to advanced
• Training duration: 2 hours and 11 minutes

Course headings

Course images

Sample video of the course

download link

Download file – 283 MB

File(s) password: www.downloadly.ir

File size

283 MB