Course Outline
Curriculum Overview Training Program Proposal
Day 1 - Foundations of AI and Python for Data Processes
• Overview of the current artificial intelligence and machine learning landscape
• The role of AI in contemporary data engineering
• Refresher on Python fundamentals for AI contexts
• Utilizing data manipulation tools such as pandas and NumPy
• Basics of API interaction and JSON data management
• Mini exercise: dataset loading and transformation
Day 2 - Core Machine Learning Concepts for Practitioners
• Principles of supervised and unsupervised learning
• Techniques for feature engineering and data preprocessing
• Fundamental model training using scikit-learn
• Evaluating model performance and understanding key metrics
• Overview of model deployment strategies
• Practical task: constructing a basic predictive model
Day 3 - Large Language Models and Prompt Engineering Basics
• Demystifying large language models and their operational mechanics
• Concepts of tokenization, context windows, and inherent limitations
• Best practices and techniques for prompt design
• Exploring zero-shot and few-shot prompting methods
• Strategies for evaluating prompts and iterative refinement
• Practical prompt engineering activities
Day 4- Creating AI Applications with LLMs
• Integrating LLM APIs within Python applications
• Managing structured outputs and function calling features
• Development of chat-based and task-oriented applications
• Introduction to retrieval augmented generation (RAG)
• Connecting LLMs to external data repositories
• Mini project: developing a basic AI assistant
Day 5 - Deploying AI Solutions for Production
• Architecting scalable AI workflows
• Embedding AI components into data pipelines
• Strategies for monitoring and enhancing model performance
• Cost management and efficient API utilization techniques
• Addressing security and responsible AI practices
• Capstone project: building 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
