Description generated based on course syllabus and open data.
Python developer: role and scope
Every website or app reflects the work of Python developers. They write and maintain code, build web applications, use frameworks and libraries, perform data analysis, and apply machine learning.
Learning modules for a Python developer
Python Basics
Syntax, variables, types, loops, functions, operators, lists, and other core constructs.
GenAI Essentials
Responsible and effective use of generative AI to accelerate common Python engineering tasks.
Course Fundamentals
Work practices and preparation for advanced topics to systematize learning and improve productivity.
Python Basics Extended
Deeper look into data types, logic, loops; debugging and code style in Python.
Git and Terminal
Terminal commands, Git version control, branching, commits, and repository workflows.
Python Core
Hands-on work with generators, iterators, decorators, and patterns central to Python engineering.
Who the Python developer path fits, and who it doesn’t
- Fits: programming beginners; developers from other languages; data analysts moving to development; those targeting backend or automation.
- Doesn’t fit: if unwilling to use the terminal, version control, testing, and read documentation in English.
Problem → outcome in Python development
- Fragmented syntax knowledge → systematic foundation via Python Basics and Basics Extended.
- Code management issues → confident Git and command-line workflows.
- Confusion with iterators and decorators → practical drills in Python Core.
- Time-consuming routine → careful use of GenAI tools with result verification.
Comparison with alternatives in Python development
- Self-study: flexible, but often lacks structure and consistent feedback.
- Short bootcamps: fast, yet limited depth and practice consolidation.
- Switching to other stacks (JavaScript/Java): broad ecosystems, but different syntax and tooling.
Outcomes after completing the modules for a Python developer
- Understanding of Python syntax, data structures, and basic algorithms.
- Skills with Git, terminal, and basic debugging.
- Knowledge of key constructs: generators, iterators, decorators, and code style principles.
- Baseline readiness for web applications, data analysis, and entry-level machine learning tasks.
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