Course Outline
Course Outline Training Proposal
Day 1 - Introduction to AI and Python for Data Workflows
• Overview of the artificial intelligence and machine learning landscape
• The role of AI in modern data engineering for government operations
• Refresher on Python fundamentals for AI applications
• Working with data using pandas and NumPy libraries
• Introduction to APIs and JSON data handling for government use cases
• Mini exercise: Loading and transforming datasets in a government context
Day 2 - Machine Learning Foundations for Practitioners
• Concepts of supervised and unsupervised learning
• Techniques for feature engineering and data preparation
• Basics of model training using scikit-learn for government datasets
• Model evaluation and performance metrics for public sector applications
• Introduction to model deployment concepts in a government setting
• Hands-on exercise: Building a simple predictive model for government use
Day 3 - Introduction to LLMs and Prompt Engineering
• Understanding large language models and their mechanisms
• Tokenization, context windows, and limitations of LLMs in government applications
• Principles and techniques for prompt design
• Zero-shot and few-shot prompting strategies for public sector tasks
• Evaluation and iteration strategies for prompts in a government environment
• Hands-on exercise: Prompt engineering for government-specific scenarios
Day 4 - Building AI Applications with LLMs
• Using LLM APIs within Python for government projects
• Concepts of structured outputs and function calling in a public sector context
• Development of chat-based and task-based applications for government use
• Introduction to retrieval augmented generation for enhancing government services
• Connecting LLMs with external data sources for government datasets
• Mini project: Building a simple AI assistant for government tasks
Day 5 - Productionizing AI Solutions
• Designing scalable AI workflows for government operations
• Integrating AI into existing data pipelines for public sector efficiency
• Monitoring and improving model performance in a government setting
• Strategies for cost optimization and efficient API usage in government projects
• Security considerations and responsible AI practices for government applications
• Final project: Building an end-to-end AI solution for government use
Testimonials (2)
Examples/exercices perfectly adapted to our domain
Luc - CS Group
Course - Scaling Data Analysis with Python and Dask
The trainer was very available to answer all te kind of question I did
