Share this link via
Or copy link
Overview
This course provides an in-depth exploration of time series analysis using Python. Students learn how to preprocess time series data, identify trends, seasonality, and cycles, and apply statistical models like ARIMA, SARIMA, and Prophet for forecasting. The curriculum covers visualization techniques, anomaly detection, and evaluation metrics to assess model performance. Practical exercises use real-world datasets to build predictive models for finance, economics, and business applications. By the end of the course, learners will be equipped to analyze and forecast time-dependent...
Syllabus
- Introduction to the Course
- Read in Data From External Data Sources
- Preprocessing & Visualising Time Series Data in Python
- Characteristics & Conditions of Time Series Data
- Basic Time Series Forecasting
- Machine Learning For Time Series
- Use Deep Learning For Time Series Data
- Miscellaneous Lectures
Instructor
Minerva Singh
Reviews
No reviews yet. Be the first to review!
Alternative Courses
Demystify complex big data technologies Compared to traditional data processing,...
Free
Organizations are pressured to become digital enterprises for good reason....
Free
You must be logged in to submit a review.