Forecasting Models and Time Series for Business in Python
Forecasting is always enticing; knowing what will happen typically leaves people in awe. Furthermore, it is critical in the corporate sector. Revenue growth and EBIT estimations are always provided by companies and are based on forecasts. It is critical that you understand why a model makes sense and the underlying assumptions that underpin it. They'll explain each model to you using words, diagrams, and metaphors, avoiding arithmetic and the Greek letters as much as possible. They will guide you through every step of the way in your journey to mastering time series and forecasting models. They will also explain all the parameters and functions that you need to use, step by step.
There is a challenge for each algorithm. That is, each approach consists of two case studies. The idea is for you to use what you've learned right away. They will provide you with a dataset and a list of steps you must follow to solve it. It's believed that this is the best method to truly embed all of the skills in you. This is one of the best online forecasting courses.
The techniques in this course are the ones it believes will be the most impactful, up-to-date, and sought-after:
- Holt-Winters
- TBATS
- SARIMAX
- TensorFlow: Structural Time Series
- Facebook Prophet
- Facebook Prophet + XGBoost
- Ensemble approach
Who is this course for?
- Professionals looking to learn about demand forecasting and time series
Requirements:
- Basic Statistics: Linear Regression, p-value
- Basic Python is desirable.
Udemy rating: 4.5/5
Enroll here: https://www.udemy.com/course/forecasting-python/
