Course Outline
Introduction to Generative AI for Government
- What is Generative AI?
- History and evolution of Generative AI
- Key concepts and terminology
- Overview of applications and potential of Generative AI for government
Fundamentals of Machine Learning for Government
- Introduction to machine learning
- Types of machine learning: Supervised, Unsupervised, and Reinforcement Learning
- Basic algorithms and models
- Data preprocessing and feature engineering for government datasets
Deep Learning Basics for Government
- Neural networks and deep learning
- Activation functions, loss functions, and optimizers
- Overfitting, underfitting, and regularization techniques in government applications
- Introduction to TensorFlow and PyTorch for government use
Generative Models Overview for Government
- Types of generative models
- Differences between discriminative and generative models
- Use cases for generative models in government operations
Variational Autoencoders (VAEs) for Government
- Understanding autoencoders
- The architecture of VAEs
- Latent space and its significance in government applications
- Hands-on project: Building a simple VAE for government data
Generative Adversarial Networks (GANs) for Government
- Introduction to GANs
- The architecture of GANs: Generator and Discriminator
- Training GANs and challenges in government contexts
- Hands-on project: Creating a basic GAN for government use
Advanced Generative Models for Government
- Introduction to Transformer models
- Overview of GPT (Generative Pretrained Transformer) models
- Applications of GPT in text generation for government communications
- Hands-on project: Text generation with a pre-trained GPT model for government reports
Ethics and Implications for Government
- Ethical considerations in Generative AI for government
- Bias and fairness in AI models used by the government
- Future implications and responsible AI in government operations
Industry Applications of Generative AI for Government
- Generative AI in art and creativity for public sector projects
- Applications in business and marketing for government agencies
- Generative AI in science and research for government initiatives
Capstone Project for Government
- Ideation and proposal of a generative AI project for government use
- Dataset collection and preprocessing for government data
- Model selection and training for government applications
- Evaluation and presentation of results to government stakeholders
Summary and Next Steps for Government
Requirements
- An understanding of fundamental programming concepts in Python
- Experience with basic mathematical principles, particularly probability and linear algebra
Audience
- Developers for government and other public sector entities
Testimonials (2)
Going over the various use cases and application of AI was helpful. I enjoyed the walkthrough of the various AI Agents.
Axel Schulz - CANARIE Inc
Course - Microsoft 365 Copilot: AI Productivity Across Word, Excel, PowerPoint, Outlook, and Teams
I liked that trainer had a lot of knowledge and shared it with us
