Forecasting Models and Time Series for Business in Python

Use time series analysis to identify patterns and trends in time series data in Python.Select appropriate forecasting models for different types of time series data in Python.Develop demand planning and forecasting models using time series analysis techniques in Python.Implement Holt-Winters exponential smoothing in Python for time series forecasting.Implement SARIMAX models for time series forecasting in Python.Utilize Facebook Prophet for forecasting future values of time series data.Apply Tensorflow Structural Time Series to forecast time series data using machine learning techniques.Implement XGBoost for time series forecasting in Python.Understand the assumptions and limitations of different time series forecasting models in Python.Evaluate the performance of different time series forecasting models in Python.Welcome to the most exciting online course about Forecasting Models in Python. I will show everything you need to know to understand the now and predict the future.Forecasting is always sexy – knowing what will happen usually drops jaws and earns admiration. On top, it is fundamental in the business world. Companies always provide Revenue growth and EBIT estimates, which are based on forecasts. Who is doing them? Well, that could be you!WHY SHOULD YOU ENROLL IN THIS COURSE?YOU WILL LEARN THE INTUITION BEHIND THE MODELS WITHOUT FOCUSING TOO MUCH ON THE MATHIt is fundamental that you know why a model makes sense and the underlying assumptions behind it. I will explain to you each model using words, graphs, and metaphors, leaving math and the Greek alphabet to a minimum.THOROUGH COURSE STRUCTURE OF MOST IMPACTFUL ECONOMETRIC TECHNIQUESThe techniques in this course are the ones I believe will be most impactful, up to date, and sought after:Holt-WintersTBATSSARIMAXTensorFlow Structural Time SeriesFacebook ProphetFacebook Prophet + XGBoostEnsemble approachWE CODE  PYTHON TOGETHER LINE BY LINEI will guide you through every step of the way. I will also explain all parameters and functions that you need to use, step by step.THE FINAL REASON IS THAT YOU PRACTICE, PRACTICE, PRACTICE.For each algorithm, there is a challenge. This means that each technique has 2 case studies. The goal is that you apply immediately what you have learned. I give you a dataset and a list of actions you need to take to solve it. I think it is the best way to really cement all the techniques in you.Did I spike your interest? Join me and learn how to predict the future!Who this course is for:Business analysts looking to improve their forecasting skills and techniques.Data scientists interested in applying time series analysis and forecasting to business problems.Marketing professionals looking to forecast future demand for products or services.Financial analysts seeking to forecast future trends and performance for businesses.Operations managers looking to improve demand planning and forecasting for their organization.