Course Outline
Introduction to Artificial Intelligence for Software Development
- Differentiating Generative AI from Predictive AI
- Applications of AI in coding, analytics, and automation
- Overview of large language models (LLMs), transformers, and deep learning frameworks
AI-Assisted Coding and Predictive Development for Government
- Utilizing AI-powered code completion and generation tools (e.g., GitHub Copilot, CodeGeeX)
- Anticipating and mitigating code bugs and vulnerabilities prior to deployment
- Automating the process of code reviews and providing optimization recommendations
Building Predictive Models for Software Applications for Government
- Understanding time-series forecasting and predictive analytics techniques
- Implementing AI models to forecast demand and detect anomalies
- Using Python, Scikit-learn, and TensorFlow for developing predictive models
Generative AI for Text, Code, and Image Generation for Government
- Working with advanced language models such as GPT and LLaMA
- Generating synthetic data, text summaries, and documentation
- Creating AI-generated images and videos using diffusion models
Deploying AI Models in Real-World Applications for Government
- Hosting AI models on platforms like Hugging Face, AWS, and Google Cloud
- Developing API-based AI services for various business applications
- Fine-tuning pre-trained AI models to address specific domain tasks
AI for Predictive Business Insights and Decision-Making for Government
- Leveraging AI-driven business intelligence and customer analytics
- Forecasting market trends and consumer behavior
- Automating workflow optimizations using AI technologies
Ethical AI and Best Practices in Development for Government
- Addressing ethical considerations in AI-assisted decision-making processes
- Detecting and mitigating bias to ensure fairness in AI models
- Implementing best practices for interpretable and responsible AI development
Hands-On Workshops and Case Studies for Government
- Implementing predictive analytics on a real-world dataset
- Constructing an AI-powered chatbot with text generation capabilities
- Deploying an LLM-based application for automation tasks
Summary and Next Steps for Government
- Recap of key takeaways from the session
- Resources and tools for further learning in AI development
- Concluding Q&A session to address any remaining questions
Requirements
- An understanding of fundamental software development concepts for government.
- Experience with any programming language, with Python being highly recommended.
- Familiarity with machine learning or artificial intelligence fundamentals is beneficial but not mandatory.
Audience
- Software developers for government agencies.
- AI/ML engineers working in public sector environments.
- Technical team leads overseeing government projects.
- Product managers interested in developing AI-powered applications for government use.
Testimonials (2)
It was fairly interactive, quite well focused on our areas of interest. It gives a good base for further development in the area
Donal Carroll - Teleflex Medical Europe Ltd
Course - Copilot for Finance and Accounting Professionals
The trainer was well prepared and had great examples.
