Forecasting and Predictive Modelling

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Overview

This workshop is designed to introduce the concepts and techniques of forecasting and predictive modelling. It is aimed at professionals and students who are interested in understanding how to use historical data to make informed predictions about future events. The course will cover various statistical and machine learning methods used in predictive analysis, providing attendees with practical skills to apply in their respective fields.

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Key Topics

• Introduction to Forecasting and Predictive Modelling

• Time Series Analysis and Trend Forecasting

• Regression Models (Linear and Logistic)

• Introduction to Machine Learning Algorithms

• Model Validation and Performance Metrics

• Practical Applications in Business, Finance, and Research

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Learning Outcomes

• Gain a solid understanding of forecasting and predictive modelling concepts.

• Learn to analyse and model time series data for trend forecasting.

• Develop skills in building and interpreting regression models.

• Get an overview of machine learning techniques used in prediction.

• Understand how to validate models and interpret their performance.

• Apply these techniques to real-world scenarios in various domains.

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Who Should Attend?

This workshop is suitable for business analysts, data analysts, researchers, and students in fields where forecasting is relevant. A basic understanding of statistics and data analysis is recommended.

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Why Attend?

• Acquire skills in high-demand areas of data analysis and prediction.

• Enhance your ability to make data-driven decisions and predictions.

• Learn practical approaches to model future trends and events.

• Stay competitive in a rapidly evolving field of predictive analytics.

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Format

A blend of theoretical instruction, case studies, and hands-on exercises using real-world data. Participants will have the opportunity to work with statistical software for practical experience in modelling and forecasting.