AI+ Sustainability Practitioner™

Kód kurzu: NPAS2010

Tato část není lokalizována

Formerly known as AI+ Sustainability™

Accelerate Sustainability with AI for smarter, greener progress

Advancing Sustainable Innovation: Apply the Power of Advanced AI
AI for Environmentally Sound Decisions: Explore carbon footprint analytics, resource optimization, and climate-impact modeling.
Strategic Sustainability Planning: Learn to build data-driven, eco-focused frameworks that support long-term environmental goals.
Practical Tools for the Future: Covers lifecycle assessment tools, emission-tracking AI, and smart energy-management systems.
Efficiency & Accountability: Improve operational efficiency, minimize waste, and accelerate your organization's progress toward a cleaner, climate-conscious future.

Odborní
certifikovaní lektoři

Mezinárodně
uznávané certifikace

Široká nabídka technických
a soft skills kurzů

Skvělý zákaznický
servis

Přizpůsobení kurzů
přesně na míru

Termíny kurzu

Počáteční datum: Na vyžádání

Garantovaný

Forma: Self-paced

Délka kurzu: 8 hodin

Jazyk: en

Cena bez DPH: 6 950 Kč

Registrovat

Počáteční datum: Na vyžádání

Garantovaný

Forma: Self-paced

Délka kurzu: 8 hodin

Jazyk: en

Cena bez DPH: 1 830 Kč

Registrovat

Počáteční
datum
Místo
konání
Forma Délka
kurzu
Jazyk Cena bez DPH
G Na vyžádání Self-paced 8 hodin en 6 950 Kč Registrovat
G Na vyžádání Self-paced 8 hodin en 1 830 Kč Registrovat
G Garantovaný kurz

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Kontakt

Popis kurzu

Tato část není lokalizována

AI Applications for Sustainability

Learn how to apply AI technologies to tackle environmental challenges such as climate change, resource depletion, and waste management.

Data-Driven Environmental Solutions

Gain skills in analyzing environmental data to create predictive models for optimizing energy use, reducing emissions, and improving sustainability.

AI in Green Technologies

Understand how AI can enhance renewable energy systems, smart grids, and eco-friendly innovations in industries like agriculture and manufacturing.

Sustainability Strategies

Learn to develop and implement AI-driven sustainability strategies that align with corporate and global environmental goals.

AI for Environmental Policy and Research

Acquire knowledge on using AI to support policy-making, climate research, and biodiversity conservation efforts.

Struktura kurzu

Tato část není lokalizována

Module 1: Introduction to AI and Sustainability

  • 1.1 Overview of Artificial Intelligence
  • 1.2 Introduction to Sustainability
  • 1.3 Sustainability Challenges
  • 1.4 AI for Green
  • 1.5 Case Study: AI Models for Climate Change Prediction
  • 1.6 Hands On: Visualizing Global CO₂ Emissions Trends with GPT

Module 2: AI Techniques for Sustainability Solutions

  • 2.1 Introduction to Machine Learning for Sustainability
  • 2.2 Supervised Learning for Environmental Impact
  • 2.3 Unsupervised Learning for Environmental Insights
  • 2.4 Reinforcement Learning for Sustainable Systems
  • 2.5 Green AI: Sustainable AI Models
  • 2.6 Hands-On

Module 3: AI for Climate Change Mitigation

  • 3.1 AI in Climate Modeling
  • 3.2 AI for Renewable Energy Integration
  • 3.3 Carbon Footprint Reduction
  • 3.4 Case Study: Optimizing Wind Turbine Operations with AI
  • 3.5 Hands-On Exercises

Module 4: AI in Sustainable Energy Systems

  • 4.1 AI for Energy Optimization
  • 4.2 Renewable Energy Integration
  • 4.3 AI in Energy Storage and Efficiency
  • 4.4 Case Study: AI-Powered Smart Grids: Optimizing Energy Distribution and Integrating Renewables
  • 4.5 Hands-On Exercises: Optimizing Smart Grid Load Balancing

Module 5: AI for Sustainable Agriculture

  • 5.1 Precision Agriculture and Resource Optimization
  • 5.2 AI for Pest and Disease Detection
  • 5.3 Sustainable Farming and Decision Support Systems
  • 5.4 Case Study: AI in Precision Agriculture
  • 5.5 Hands-On: Predicting Crop Yields with Machine Learning

Module 6: AI in Waste Management and Circular Economy

  • 6.1 AI for Waste Sorting and Recycling
  • 6.2 AI for Waste-to-Energy Solutions
  • 6.3 Circular Economy and Resource Recovery
  • 6.4 Case Study: AI for Waste Sorting and Recycling
  • 6.5 Hands-On: Building a Waste Sorting Classifier with AI

Module 7: AI for Biodiversity Conservation and Environmental Monitoring

  • 7.1 AI in Remote Sensing for Environmental Monitoring
  • 7.2 Wildlife Tracking and Conservation
  • 7.3 AI for Ecosystem Health Monitoring
  • 7.4 Case Study: AI for Deforestation Monitoring
  • 7.5 Hands-On: Detecting Deforestation Using Satellite Imagery

Module 8: AI for Water Resource Management

  • 8.1 AI for Water Consumption Prediction
  • 8.2 AI for Smart Irrigation Systems
  • 8.3 Water Quality Monitoring and Analysis
  • 8.4 Case Study: AI for Smart Irrigation Systems
  • 8.5 Hands-On: Optimizing Irrigation Systems with AI

Module 9: AI for Sustainable Cities and Smart Urban Development

  • 9.1 AI in Smart City Infrastructure
  • 9.2 Sustainable Mobility and Transportation
  • 9.3 AI in Urban Resource Optimization
  • 9.4 Case Study: AI for Urban Air Quality Monitoring
  • 9.5 Hands-On: Optimizing Traffic Flow and Reducing Emissions with AI-Driven Smart Traffic Management

Předpokládané znalosti

Tato část není lokalizována

  • AI Fundamentals: You’re familiar with core AI concepts and algorithms. 
  • Sustainability Awareness: You understand key environmental challenges and solutions. 
  • Data Analytics Skills: You can analyze and interpret data effectively. 
  • Environmental Science Knowledge: You understand key environmental principles and sustainability frameworks. 
  • Programming Ability: You can work with Python or a similar language. 

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