Software Engineering and AI Programming

Configure Python and Visual Studio Code on Windows and run a Python script from PowerShell.

Evaluate Python expressions that use numeric, string, Boolean, and type-conversion operations.

Read user input and produce formatted console output in a Python program.

Implement decision logic with conditional statements and Boolean expressions.

Implement repeated operations with for loops and while loops.

Define and call functions that use parameters and return values.

Select and use lists or tuples to represent ordered data.

Select and use dictionaries or sets to organize and look up data.

Translate a small software requirement into inputs, processing steps, outputs, and pseudocode.

Apply string methods, indexing, and slicing to clean and extract text data.

Import standard-library modules and reuse functions from a custom Python module.

Read and write text files safely with pathlib and context managers.

Parse, modify, and generate JSON data with Python.

Read, transform, and write tabular data in CSV files.

Catch and raise specific exceptions to handle expected failures.

Create a command-line interface with arguments and help text using argparse.

Create an isolated Python virtual environment and reproduce its dependencies with pip.

Initialize a Git repository and create focused commits with meaningful messages.

Use Git branches and resolve a simple merge conflict.

Publish a repository to GitHub and complete a pull-request workflow.

Exclude generated files and protect credentials with .gitignore and environment variables.

Add type hints and docstrings that clarify a function's contract.

Refactor a single-file script into cohesive functions and modules.

Write a README that enables another developer to install and run a project.

Define a Python class with a constructor, instance attributes, and instance methods.

Enforce valid object state with properties and validation logic.

Represent simple data-focused objects with dataclasses.

Model a has-a relationship between objects using composition.

Use inheritance only where subclasses satisfy the parent class's behavioral contract.

Convert domain objects to and from dictionary or JSON representations.

Separate domain logic from console, file, or network input and output.

Use a Python traceback to locate and explain the source of a runtime failure.

Inspect program state with breakpoints, stepping, and watches in the Visual Studio Code debugger.

Record useful diagnostic information with appropriately leveled log messages.

Write pytest unit tests that follow arrange-act-assert structure.

Use parametrized tests to check normal, boundary, and invalid inputs.

Create pytest fixtures for reusable test setup and cleanup.

Mock a filesystem or HTTP dependency to make a unit test deterministic.

Use a coverage report to identify and test an unverified code path.

Build a previewable file-renaming automation with pathlib.

Extract structured values from text with regular expressions.

Read and update an Excel workbook with openpyxl.

Call a public web API from Python with query parameters and headers.

Consume a paginated API without duplicating or skipping records.

Add timeouts, retries, and clear failure reporting to a network automation.

Run a Python automation on a schedule with Windows Task Scheduler.

Package an automation as a configurable command-line tool with logging.

Explain how clients, servers, HTTP requests, and HTTP responses interact in a web application.

Inspect HTTP methods, URLs, headers, bodies, and status codes with an API client.

Translate a set of application resources into consistent REST endpoint paths and methods.

Create and run a FastAPI application with a health-check endpoint.

Use FastAPI path and query parameters to handle request inputs.

Validate JSON request bodies with Pydantic models.

Implement create, read, update, and delete endpoints with an in-memory data store.

Return appropriate HTTP status codes and structured error responses.

Design a relational schema using tables, primary keys, foreign keys, and constraints.

Insert, retrieve, update, and delete rows with SQL statements.

Filter, sort, and limit SQL query results.

Summarize grouped data with SQL aggregate functions.

Combine related table rows with inner and outer joins.

Execute parameterized SQLite queries safely from Python.

Map relational records to Python objects with SQLAlchemy models and sessions.

Create and apply a database schema migration with Alembic.

Separate FastAPI routing, business logic, and data access into router, service, and repository layers.

Connect FastAPI create, read, update, and delete operations to SQLAlchemy persistence.

Implement user registration that stores a securely hashed password.

Implement login and protect an endpoint with JSON Web Token authentication.

Enforce resource ownership so authenticated users can access only permitted records.

Write API integration tests against an isolated test database.

Containerize a FastAPI application and its runtime configuration with Docker.

Deploy the containerized API to a managed service and verify its health and logs.

Install a Java development kit and run a Java program from an integrated development environment.

Translate variable declarations, expressions, conditionals, and loops from Python into Java.

Define and call Java methods with typed parameters and return values.

Use Java arrays, lists, maps, and sets to represent application data.

Define a Java class with constructors, encapsulated fields, and instance methods.

Use a Java interface to implement polymorphic behavior.

Handle expected failures with Java exception handling.

Build a small Maven project and verify one class with a JUnit test.

Estimate the time and space complexity of common loops and collection operations using Big O notation.

Solve a small array or string problem with a step-by-step algorithm.

Use a hash map or set to improve the efficiency of a lookup-based problem.

Solve a last-in-first-out or first-in-first-out problem with a stack or queue.

Apply sorting or binary search to solve a problem over ordered data.

Communicate assumptions, test cases, and complexity while solving a coding-interview problem.

Tailor a junior software-engineering résumé and project selection to a specific job description.

Prepare concise STAR stories and technical explanations of portfolio decisions.

Explain the capabilities, limitations, privacy risks, and usage costs of a language-model API.

Store an AI provider credential securely and make an authenticated model request.

Construct a prompt with clear instructions, context, and user input.

Request structured model output and validate it with a Pydantic schema.

Handle model timeouts, rate limits, malformed output, and provider failures.

Add an AI-backed feature endpoint to an existing FastAPI application.

Test AI-integrated application logic with a mocked model provider.

Create a portfolio-ready project presentation covering architecture, setup, API examples, tests, and engineering trade-offs.