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    Forecasting Models and Time Series for Business in Python

    Posted By: yoyoloit
    Forecasting Models and Time Series for Business in Python

    Forecasting Models and Time Series for Business in Python
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
    Genre: eLearning | Language: English + srt | Duration: 123 lectures (8h 11m) | Size: 2.8 GB

    Learn Holt-Winters, Arima, Sarimax, Tensorflow Time Series, Facebook Prophet, XGBoost for Demand Planning & Forecasting What you'll learn:
    Holt-Winters
    TBATS
    SARIMAX
    Facebook Prophet
    Tensorflow Structural Time Series
    XGBoost
    Time Series Analysis
    Demand Planning and Forecasting

    Requirements
    Basic Statistics: Linear regression, p-value
    Basic Python desirable

    Description
    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 MATH

    It 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 TECHNIQUES

    The techniques in this course are the ones I believe will be most impactful, up to date, and sought after:

    Holt-Winters

    TBATS

    SARIMAX

    TensorFlow Structural Time Series

    Facebook Prophet

    Facebook Prophet + XGBoost

    Ensemble approach

    WE CODE TOGETHER LINE BY LINE

    I 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
    Professionals looking to learn about Demand Forecasting and Time Series