Agile Leadership & Python + HTML, CSS & AI

Course overview

Introductory sentence: This Python course combines practical programming with Agile Leadership, Scrum methods, frontend techniques, and AI applications, enabling you to use Python purposefully for automation, data analysis, and product-related prototypes. Python: practical, agile, and AI-integrated In this Python course, you will learn the core competencies from the basics to application in productive work processes: variables, data types, control structures, functions, data structures (lists, dictionaries), error handling, and modularization. Python provides the foundation for automation, data processing, and the integration of AI solutions. Building on this, you will develop practical Python applications: scripting for process automation, data analysis with pandas and numpy, visualization with matplotlib/plotly, and small web APIs with Flask to connect Python-based services with HTML/CSS frontends. This way, you will understand how Python and frontend development interact. The course links Python with AI fundamentals: data preparation, introduction to machine learning workflows, use of scikit-learn and simple deep learning pipelines, prompt engineering for generative models, and the use of AI tools for code assistance. Participants will learn to integrate Python and AI responsibly, recognize bias, and consider data protection aspects. Agile Leadership and Scrum principles accompany the technical work: you will learn how Scrum teams deliver agilely with Python projects, the roles of Product Owner, Scrum Master, and Developer, and how responsibility, prioritization, and continuous improvement are shaped in the context of technical development. Python development is thus embedded in agile product development. Practical projects promote transfer and portfolio: you will develop small but meaningful projects in Python (automation script, data analysis, chatbot prototype, responsive web frontend with HTML/CSS/SASS/Bootstrap), practice debugging and testing, use versioning and deployment methods, and document results for professional roles such as Python Developer, Data Practitioner, or Product Owner with technical understanding. Learning objectives with direct application: you will learn Python core concepts, apply libraries for data processing, develop reusable, maintainable code, integrate AI functions, and connect Python backends with frontend techniques. The goal is for you to independently plan Python projects, set priorities agilely, assess risks, and implement them considerately for stakeholders. Methodology and working style: hands-on exercises, practical case studies, and collaborative code reviews convey best practices. Prompt engineering for coding assistance, automated testing, and refactoring with Python tools will be practiced. Agile techniques support team coordination and rapid iteration of prototypes. Professional relevance and perspectives: the course strengthens skills for roles such as Python Developer, Data Analyst, AI User, or A…

Upcoming dates

• 2026-09-27T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Virtuelles Klassenzimmer