AI Engineering
Learn LLMs, RAG, agents, secure tools, and production AI through practical insurance examples.
Python basics, lists, dictionaries, and sets
Python is a dynamically typed language widely used by AI libraries. A list is an ordered collection, a dictionary maps keys to values, and a set stores unique hashable values. Python uses indentation to define code blocks rather than braces.
Functions, classes, modules, and exceptions
Functions package operations; classes group state and behavior; modules are importable Python files or packages. Exceptions represent errors that interrupt normal control flow until handled. These serve the same broad purposes as functions, classes, imports,…
Virtual environments, pip, and project structure
A virtual environment isolates a project's Python packages. pip installs packages into the selected environment. Project structure separates API routes, business services, adapters, and tests so the AI code does not become one notebook-sized script.
Async/await, type hints, and HTTP clients
Python async def creates a coroutine function; await lets other work proceed while an awaitable operation waits. Type hints describe expected inputs and outputs for developers and type checkers. HTTP clients such as HTTPX provide asynchronous requests,…
Pydantic and FastAPI
Pydantic validates data against Python model definitions. FastAPI uses declared routes and schemas to build HTTP services with validation and API documentation. Think of Pydantic as a role similar to Zod and FastAPI as a Python web framework with typed…
Basic NumPy, Pandas, and Jupyter
NumPy provides efficient numerical arrays and vector operations. Pandas provides table-like data structures for cleaning and analyzing datasets. Jupyter provides interactive notebooks that mix code, results, and explanations.
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