Course Outline
Course Outline Training Proposal
Day 1 - Foundations of AI and Python in Data Workflows
• Surveying the current landscape of artificial intelligence and machine learning
• The pivotal role of AI within contemporary data engineering
• Refreshing Python fundamentals for AI-specific applications
• Manipulating data using pandas and NumPy libraries
• Basics of API interaction and JSON data processing
• Practical exercise: loading and transforming datasets
Day 2 - Practical Machine Learning Foundations
• Core concepts of supervised and unsupervised learning
• Techniques for feature engineering and data preparation
• Basics of model training using scikit-learn
• Evaluating models and interpreting performance metrics
• Introduction to foundational concepts in model deployment
• Hands-on exercise: developing a basic predictive model
Day 3 - Exploring LLMs and Prompt Engineering
• Demystifying large language models and their operational mechanics
• Understanding tokenization, context windows, and inherent limitations
• Core principles and techniques for effective prompt design
• Implementing zero-shot and few-shot prompting strategies
• Strategies for evaluating and iterating on prompts
• Practical prompt engineering exercises
Day 4 - Developing AI Applications with LLMs
• Leveraging LLM APIs within Python environments
• Concepts of structured outputs and function calling
• Constructing chat-based and task-oriented applications
• Introduction to retrieval-augmented generation
• Linking LLMs with external data sources
• Mini-project: building a basic AI assistant
Day 5 - Operationalizing AI Solutions
• Architecting scalable AI workflows
• Embedding AI capabilities within data pipelines
• Monitoring and enhancing model performance
• Strategies for cost optimization and API management
• Security protocols and responsible AI practices
• Final project: developing a comprehensive 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
