Udemy

CO₂ Emissions Forecasting with Shallow Neural Nets in Python

立即報名
  • 1,375 名學生
  • 更新於 11/2025
5.0
(161 個評分)
CTgoodjobs 嚴選優質課程,為職場人士提升競爭力。透過本站連結購買Udemy課程,本站將獲得推廣佣金,有助未來提供更多實用進修課程資訊給讀者。

課程資料

報名日期
全年招生
課程級別
學習模式
修業期
4 小時 30 分鐘
教學語言
英語
授課導師
Energy Data Scientist, PhD
評分
5.0
(161 個評分)
5次瀏覽

課程簡介

CO₂ Emissions Forecasting with Shallow Neural Nets in Python

Build Accurate Time Series Forecasts with Python - Energy Sector Application


EXTRAS

There are entire books and hundreds of papers & Python models available to download in my Skool community. I also have Financial Times articles , and over 100 online courses on Python modelling of energy markets, energy investments  etc. 

I also post job opportunities for the wider energy sector.

The value is immense!

I also do supervision which means when you start learning a course, you can message me as many questions as you need, any time e.g. daily.

This link below offers 7 days free access to this Skool community. No obligation to pay anything in advance. At the end of the 7- day period, you can decide whether you want to continue at $25/month or just cancel and leave.
Honestly, the $25/month is a very generous price . You will realise it once you join. Universities , colleges, would charge thousands! This is really a unique opportunity of immense value, at a really low cost!

Link:  www     [dot]      skool      [dot]       com/software-school-for-energy-7177




WHO I AM: 

Researcher and educator specializing in energy data science (PhD in Energy)


REGULAR ENHANCEMENTS:

Course reviewed periodically with updates.



What You'll Learn:

  • How to build a Shallow Neural Network model in Python that can forecast CO₂ emissions

  • How to achieve high accuracy in the forecasts that you will produce

  • How to work with World Bank historical data

  • How to implement advanced statistical tests

  • How to apply your model to real-world cases (India, China, USA, UK, European Union analysis)



Perfect For:

  • Environmental consultants and analysts

  • Energy economists and policy makers

  • Data scientists in sustainability

  • Climate professionals


Why This Matters:

With net-zero targets and mandatory carbon reporting, professionals who can produce credible emissions forecasts are in high demand. Master the skills that set you apart in the growing climate economy. Companies now require carbon footprint assessments for regulatory compliance and ESG reporting. Governments need emissions projections for policy planning. Consultancies charge premium rates for these capabilities. Whether you're advancing your current career or transitioning into sustainability, these practical forecasting skills open doors to roles paying $150,000-250,000+ in the rapidly expanding green economy.

課程章節

  • 6 個章節
  • 31 堂課
  • 第 1 章 Introduction
  • 第 2 章 Data Preprocessing
  • 第 3 章 Dataset split
  • 第 4 章 Dataset scaling
  • 第 5 章 Shallow Neural Networks
  • 第 6 章 Conclusion

課程內容

  • Build Shallow Neural Network models to forecast CO2 emissions using Python
  • Apply a proven 10-step methodology for creating statistically sound and reliable forecasts
  • Work with real World Bank data to analyze emissions trends for India, China, USA, UK, EU and global averages
  • Master essential statistical tests including overfitting analysis, naive model benchmarking, and sensitivity analysis
  • Quantify forecast uncertainty using confidence intervals and error metrics like MAPE
  • Create publication-ready visualizations of historical trends and future projections
  • Understand when Shallow Neural Network modelling is appropriate for time series forecasting vs other methods
  • Implement best practices for model validation, hyperparameter tuning, and results interpretation


評價

  • A
    Allan Huber
    5.0

    The final project was challenging but incredibly rewarding—a great way to cement knowledge.

  • R
    Royal Glass
    5.0

    I loved how the course built up from basics to advanced concepts seamlessly.

  • F
    Felix Osborne
    5.0

    A perfect blend of theory, coding, and real-world applications—highly recommended!

  • R
    Remy Johnston
    5.0

    The instructor’s clear explanations made even the toughest topics digestible

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