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.
 21 Hours

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