Introduction
Revolutionize sustainability projects with AI
()
1. The Basic of AI for Sustainability
Understanding AI's role in sustainable solutions
()
Data engineering: Key concepts and tools
()
Introduction to Google Colab and its application
()
Hands-on: Setting up your first AI model in Google Colab
()
Integrating AI with data engineering workflows
()
Challenge: Build a simple AI model for energy efficiency
()
Solution: Building the AI model for energy efficiency
()
2. Advanced Data Collection Techniques
Techniques for effective data collection
()
Using IoT for sustainability data collection in Google Colab
()
Processing and cleaning IoT data
()
Challenge: Design a data collection strategy
()
Solution: Effective data collection strategies
()
3. Implementing Sustainable AI Solutions
Scaling AI for large-scale sustainability projects
()
AI in waste management: Case studies
()
Integrating AI with renewable energy sources
()
Challenge: Develop an AI solution for water conservation
()
Solution: AI for water conservation
()
4. Optimization and Automation
Using AI to optimize resource allocation
()
Automating sustainability processes with Google Colab
()
Challenge: Automate an energy-saving system
()
Solution: Automating energy efficiency
()
5. Application of AI in Smart Cities
AI technologies in urban development
()
Smart city case studies
()
Challenge: Implement AI in smart city project
()
Solution: AI application in urban settings
()
6. Ethics and Future Directions
Ethical considerations in AI development
()
Ethical dilemmas in AI projects
()
Analyzing and resolving ethical dilemmas
()
Guidance on ethical decision-making
()
Visualizing the decision-making process
()
Conclusion
Moving forward
()
How to continue learning and exploring further
()
Ex_Files_Leveraging_AI_and_Data_Engineering_Sustainable_Solutions.zip
(4.9 MB)