Course Outline
Introduction to Time Series Analysis
- Overview of time series data
- Key components of time series: trend, seasonality, and noise
- Configuring Google Colab for time series analysis
Exploratory Data Analysis for Time Series
- Visual representations of time series data
- Breaking down time series components
- Identifying seasonality and trends
ARIMA Models for Time Series Forecasting
- Understanding ARIMA (AutoRegressive Integrated Moving Average)
- Selecting optimal parameters for ARIMA models
- Building ARIMA models using Python
Introduction to Prophet for Time Series Forecasting
- Overview of Prophet in the context of time series forecasting
- Implementing Prophet models within Google Colab
- Incorporating holidays and special events into forecasts
Advanced Forecasting Techniques
- Managing missing data in time series
- Multivariate time series forecasting methods
- Enhancing forecasts with external regressors
Evaluating and Optimizing Forecast Models
- Performance metrics for assessing time series forecasts
- Optimizing ARIMA and Prophet models
- Cross-validation and backtesting strategies
Real-world Applications of Time Series Analysis
- Case studies illustrating time series forecasting
- Practical exercises using real-world datasets
- Future pathways for time series analysis in Python
Summary and Next Steps
Requirements
- Intermediate proficiency in Python programming
- Familiarity with fundamental statistics and data analysis methodologies
Target Audience
- Data analysts
- Data scientists
- Professionals involved with time series data
Testimonials (3)
Learning that the QGIS and a tool that can used by other different professionals such land survey
Bame Duncan Koko - Bentel Technologies (Pty) Ltd
Course - QGIS for Geographic Information System
How to use open satellites data for real applications
Tshering Dorji - Druk Holding and Investments
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Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
