Python Developer for AI Applications

Course overview

Python developers for AI applications implement language models and AI services using the Python programming language to create usable tools. The training teaches how to transform a professional requirement into a functional, AI-supported prototype. Python Basics for Working with AI The introduction lays the linguistic and technical foundations for all subsequent modules. - Data structures, functions, and modules for AI scripts - Working with libraries and package management - Handling JSON, CSV, and structured data sources Connecting Language Models via Interfaces - Calls to ChatGPT, Claude, and Gemini from Python - Controlling prompt templates, parameters, and response formats - Error handling, cost control, and response validation - Chaining multiple model calls into a workflow From Script to AI Tool Individual calls evolve into small applications for professional use. - Text summarization, classification, and extraction as use cases - Automated evaluation of documents and tables - Simple user interfaces and output formats for professional users - Human-in-the-loop: Incorporating review steps and approvals Quality, Law, and Operations - Testing and evaluating AI outputs before use - Handling personal data, GDPR, and EU AI Act in daily development - Documentation of prompts, versions, and results Retrieval and Working with Own Data Many use cases require answers from company-specific sources rather than from model knowledge. - Reading, breaking down, and preparing documents for queries - Embeddings and similarity search for precise findings - Generating responses with source references and reducing hallucinations - Recognizing the limits of the approach and typical quality issues Tools and Work Environment - Development environment, notebooks, and version control with Git - Libraries for HTTP requests, data processing, and output formats - Reusable function blocks for recurring AI tasks - Safely storing and using secrets like access keys Handing Over and Further Development - Structuring and commenting runnable scripts in a traceable manner - Writing brief operating instructions for colleagues - Adapting applications to new models and interface versions Integration in the Company - Collaboration with departments during requirement gathering and acceptance - Coordination with IT on approvals, data access, and operational issues Upon completion, participants will be able to independently plan, implement, and operate AI-supported evaluations and small applications using Python in their daily work.

Upcoming dates

• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Virtuelles Klassenzimmer
• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Frankfurt am Main · Hybrid Learning
• 2026-11-03T23:00:00.000Z · 2027-07-03T22:00:00.000Z · Virtuelles Klassenzimmer
• 2026-11-03T23:00:00.000Z · 2027-07-03T22:00:00.000Z · Frankfurt am Main · Hybrid Learning
• 2026-11-17T23:00:00.000Z · 2027-01-19T23:00:00.000Z · Virtuelles Klassenzimmer