Course Outline
Course Outline Training Proposal
Day 1 - Introduction to AI and Python for Data Workflows
• An overview of the current artificial intelligence and machine learning landscape
• The evolving role of AI in contemporary data engineering
• A refresher on Python fundamentals specifically for AI applications
• Data manipulation techniques using pandas and NumPy
• Fundamentals of APIs and handling JSON data
• A brief exercise focused on loading and transforming datasets
Day 2 - Machine Learning Foundations for Practitioners
• Key concepts in supervised and unsupervised learning
• Techniques for feature engineering and data preparation
• Essential model training practices using scikit-learn
• Evaluating models and interpreting performance metrics
• An introduction to the concepts of model deployment
• A hands-on session to build a basic predictive model
Day 3 - Introduction to LLMs and Prompt Engineering
• Gaining an understanding of how large language models function
• Exploring tokenization, context windows, and inherent limitations
• Core principles and techniques for prompt design
• Application of zero-shot and few-shot prompting methods
• Strategies for evaluating prompts and iterative improvement
• Practical prompt engineering exercises
Day 4- Building AI Applications with LLMs
• Utilizing LLM APIs within Python environments
• Concepts of structured outputs and function calling
• Developing chat-based and task-oriented applications
• An introduction to retrieval-augmented generation
• Connecting LLMs with external data sources
• A mini project involving the creation of a basic AI assistant
Day 5 - Productionizing AI Solutions
• Designing scalable AI workflows
• Integrating AI components into existing data pipelines
• Monitoring systems and enhancing model performance
• Strategies for cost optimization and efficient API usage
• Considerations for security and responsible AI practices
• A capstone project building a complete, end-to-end AI solution
Testimonials (2)
The trainer was very available to answer all te kind of question I did
Caterina - Stamtech
Course - Developing APIs with Python and FastAPI
Trainer develops training based on participant's pace
