Course Outline
Program Structure Instructional Roadmap
Day 1 - AI and Python Foundations for Data Operations
• Survey of the artificial intelligence and machine learning ecosystem
• The role of AI in contemporary data engineering
• Python refresher focused on AI-specific applications
• Data manipulation utilizing pandas and NumPy
• Exploration of API interactions and JSON processing
• Practical task involving dataset ingestion and transformation
Day 2 - Machine Learning Essentials for Practitioners
• Concepts in supervised and unsupervised learning
• Strategies for feature engineering and data preparation
• Core model training techniques with scikit-learn
• Model assessment and performance analysis
• Overview of model deployment strategies
• Practical exercise: constructing a basic predictive model
Day 3 - LLM Mechanics and Prompt Engineering
• Deep dive into large language model functionality
• Tokenization, context windows, and operational boundaries
• Best practices and methods for prompt design
• Application of zero-shot and few-shot prompting
• Techniques for prompt evaluation and iterative improvement
• Practical exercises in prompt engineering
Day 4 - Architecting AI Applications with LLMs
• Implementing LLM APIs within Python
• Managing structured outputs and function calling
• Development of chat-based and task-oriented applications
• Introduction to Retrieval Augmented Generation
• Integration of LLMs with external data repositories
• Mini-project: building a basic AI assistant
Day 5 - Productionizing AI Solutions
• Designing scalable AI operational flows
• Embedding AI into established data pipelines
• Monitoring and enhancing model performance
• Cost efficiency and API utilization tactics
• Security protocols 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
