Course Introduction Preview Module 1: Fundamentals of Neural Networks
- 1.1 Introduction to Neural Networks
- 1.2 Neural Network Architecture
- 1.3 Hands-on: Implement a Basic Neural Network
Module 2: Neural Network Optimization
- 2.1 Hyperparameter Tuning
- 2.2 Optimization Algorithms
- 2.3 Regularization Techniques
- 2.4 Hands-on: Hyperparameter Tuning and Optimization
Module 3: Neural Network Architectures for NLP
- 3.1 Key NLP Concepts
- 3.2 NLP-Specific Architectures
- 3.3 Hands-on: Implementing an NLP Model
Module 4: Neural Network Architectures for Computer Vision
- 4.1 Key Computer Vision Concepts
- 4.2 Computer Vision-Specific Architectures
- 4.3 Hands-on: Building a Computer Vision Model
Module 5: Model Evaluation and Performance Metrics
- 5.1 Model Evaluation Techniques
- 5.2 Improving Model Performance
- 5.3 Hands-on: Evaluating and Optimizing AI Models
Module 6: AI Infrastructure and Deployment
- 6.1 Infrastructure for AI Development
- 6.2 Deployment Strategies
- 6.3 Hands-on: Deploying an AI Model
Module 7: AI Ethics and Responsible AI Design
- 7.1 Ethical Considerations in AI
- 7.2 Best Practices for Responsible AI Design
- 7.3 Hands-on: Analyzing Ethical Considerations in AI
Module 8: Generative AI Models
- 8.1 Overview of Generative AI Models
- 8.2 Generative AI Applications in Various Domains
- 8.3 Hands-on: Exploring Generative AI Models
Module 9: Research-Based AI Design
- 9.1 AI Research Techniques
- 9.2 Cutting-Edge AI Design
- 9.3 Hands-on: Analyzing AI Research Papers
Module 10: Capstone Project and Course Review
- 10.1 Capstone Project Presentation
- 10.2 Course Review and Future Directions
- 10.3 Hands-on: Capstone Project Development
Optional Module: AI Agents for Architect
- 1. Understanding AI Agents
- 2. Case Studies
- 3. Hands-On Practice with AI Agents
Tools you will explore
- AutoGluon
- ChatGPT
- SonarCube
- Vertex AI
