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 role of AI in contemporary data engineering practices
• A Python fundamentals review focused on AI applications
• Data manipulation using pandas and NumPy
• Basics of API interaction and JSON data handling
• Practical exercise: Loading and transforming datasets
Day 2 - Machine Learning Foundations 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 quality through evaluation and performance metrics
• Introduction to key concepts in model deployment
• Practical exercise: Building a basic predictive model
Day 3 - Introduction to LLMs and Prompt Engineering
• Understanding the inner workings of large language models
• Key concepts: Tokenization, context windows, and system limitations
• Principles and techniques for effective prompt design
• Application of zero-shot and few-shot prompting methods
• Strategies for prompt evaluation and iterative improvement
• Practical exercise: Applying prompt engineering techniques
Day 4- Building AI Applications with LLMs
• Leveraging LLM APIs within Python environments
• Concepts of structured outputs and function calling
• Developing both chat-based and task-oriented applications
• Introduction to retrieval-augmented generation
• Linking LLMs with external data sources
• Mini project: Creating a simple AI assistant
Day 5 - Productionizing AI Solutions
• Architecting scalable AI workflows
• Embedding AI capabilities into data pipelines
• Monitoring model performance and implementing improvements
• Strategies for cost optimization and efficient API utilization
• Considerations for security and responsible AI practices
• Capstone project: Developing 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
