Course Outline
Course Outline Training Proposal
Day 1 - Fundamentals of AI and Python for Data Workflows
• Overview of the current artificial intelligence and machine learning landscape
• The significance of AI within contemporary data engineering
• A refresher on Python fundamentals for AI applications
• Data manipulation using pandas and NumPy
• Basics of API interaction and JSON data processing
• Mini exercise: loading and transforming datasets
Day 2 - Machine Learning Essentials for Practitioners
• Core concepts of supervised and unsupervised learning
• Techniques for feature engineering and data preparation
• Fundamentals of model training with scikit-learn
• Assessing model performance through evaluation metrics
• Introductory concepts in model deployment
• Practical session: building a basic predictive model
Day 3 - Introduction to LLMs and Prompt Engineering
• Exploring large language models and their underlying mechanics
• Understanding tokenization, context windows, and inherent limitations
• Key principles and techniques in prompt design
• Zero-shot and few-shot prompting strategies
• Methods for prompt evaluation and iterative refinement
• Practical prompt engineering exercises
Day 4- Developing AI Applications with LLMs
• Integrating LLM APIs within Python
• Concepts of structured outputs and function calling
• Creation of chat-based and task-oriented applications
• Introduction to retrieval-augmented generation
• Linking LLMs to external data sources
• Mini project: developing a basic AI assistant
Day 5 - Scaling AI Solutions for Production
• Architecting scalable AI workflows
• Embedding AI into existing data pipelines
• Strategies for monitoring and enhancing model performance
• Cost-efficiency and API usage best practices
• Security protocols and responsible AI practices
• Capstone project: constructing 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
