Course overview
Description generated based on course syllabus and open data.
Python is a general-purpose programming language for web development (Django, Flask), data work, automation and artificial intelligence. The learning format includes regular live online classes, practice, homework and a course project.
Python Developer + AI course syllabus
Python Starter (beginner)
Algorithmics, data types, collections, conditionals and loops, functions, file I/O.
Git fundamentals
Branches, commits, pull/merge, team workflows, basic conflict resolution.
Python Basic
OOP, modules and packages, exceptions, working with APIs, unit testing.
AI Skills for Python Developer
LLM principles, prompting, generating helper code and tests, integrating AI via API into small projects.
Python Advanced
Iterators and generators, decorators, context managers, async, type hints.
Databases and SQL (PostgreSQL)
Schema design, SQL queries, indexes, transactions, basics of query optimization.
Django
Models, routing, templates, ORM, simple REST APIs, basic security settings.
Python Developer capstone project
A small application using Python and/or Django, database integration, documentation and tests.
IT English and Business English
Developer-focused vocabulary, terminology, team and stakeholder communication.
Python + AI group learning format
- 3 live online classes per week on a fixed schedule.
- Hands-on tasks and homework after each topic.
- Class recordings and materials for review.
- Mentor feedback within the group.
Who this Python Developer + AI course suits
- Beginners seeking structured Python learning from scratch.
- Professionals from adjacent fields (analytics, management, marketing, finance) to automate tasks.
- Anyone moving into Django web dev or integrating AI tools.
- Junior developers needing practice with Git, SQL, APIs and testing.
Who may not benefit from Python Developer + Artificial Intelligence training
- Those unable to commit time to regular classes and homework.
- Those needing only a narrow stack without Python or AI.
- Those preferring fully self-paced study without group interaction.
Problem → outcome with Python and AI
- Problem: No study structure. Outcome: Clear path from Python basics to Django, SQL and AI practices.
- Problem: Hard to apply knowledge. Outcome: Practical tasks and a Python Developer-level capstone.
- Problem: Uncertainty using LLMs. Outcome: Foundational prompting and API integration skills.
- Problem: Lack of team tooling. Outcome: Git workflow, branching and change review.
Python Developer + AI: comparison with alternatives
- Self-study: flexible but prone to topic gaps; the course connects topics in sequence.
- Standalone video courses: fast start but little systematic practice; here practice follows each topic.
- Other languages (JS/Java): suited to their domains; Python remains a base for AI, automation and rapid development.
- Short bootcamps: high load; here the load is spread across modules and weeks.
What the Python Developer + AI course builds
- Understanding of Python syntax, OOP, error handling, modular code.
- Git skills and team collaboration.
- SQL practice and PostgreSQL design, using an ORM.
- Web apps with Django and simple REST APIs.
- LLM basics: prompting, generative workflows, API integrations.
- A small application as a Python Developer capstone.
- Technical communication in English (IT English, Business English).
