Applied AI Engineer Study

Hands-on exercises and small projects documenting my journey toward becoming an Applied AI Engineer. This repository includes Python fundamentals, Bash scripting, and LangGraph examples, with room to grow into automation, machine learning, generative AI, and deployment.

Repository structure

.
├── bash/       # Linux command-line and system-administration exercises
├── LangGraph/  # LangGraph examples using Groq
└── python/     # Python fundamentals and small programming exercises

Python exercises

The python/ directory contains standalone examples covering:

• VAT calculations: check_vat.py
• Iterating over paired lists: enumerate-food.py
• The nonlocal keyword and nested functions: nonlocal_keyword.py
• A temperature loop: tea-heating.py
• Conditional temperature and device-state checks: themostat-alert.py
• match/case selection for train seats: train-info.py
• Coupon discounts: user-discount.py
• Banking inheritance practice: banking_inheritance.py and checking_account_inheritance.py

Run an exercise with Python 3:

python python/check_vat.py

train-info.py uses structural pattern matching and requires Python 3.10 or newer. Some exercises prompt for input; follow the prompts in the terminal.

LangGraph examples

The LangGraph/ directory contains:

• chat.py: a simple graph with chatbot and weather nodes.
• ai_llm.py: a LangGraph workflow that calls a Groq chat model.

Setup and run

From the repository root, create and activate a virtual environment, then install the project dependencies:

cd LangGraph
py -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install -r requirements.txt

Create a .env file in LangGraph/ and add your Groq API key:

GROQ_API_KEY=your-groq-api-key

Run either example from the LangGraph/ directory:

python chat.py
python ai_llm.py

ai_llm.py sends a request to Groq and requires a valid API key. Keep the key private; .env and .venv/ are excluded from Git.

Bash exercises

The bash/ directory contains scripts for:

• Creating a timestamped archive backup: backupfile-script.sh
• Renaming .txt files to .md: bulk-rename.sh
• Checking root filesystem usage: disk-monitor.sh
• Displaying a system health summary: healthdashboard.sh
• Navigating a simple system-information menu: interactive-menu.sh
• Checking whether a local system user exists: user-check.sh

Run a script from a Bash-compatible environment:

bash bash/disk-monitor.sh

These scripts are intended for Linux or a compatible environment such as WSL. Some use system utilities or paths that may not be available on other operating systems. Review a script before running it, especially when it reads, modifies, or archives files.

Learning goals

• Build practical programming and automation skills.
• Strengthen Linux, Bash, and Python fundamentals.
• Progress toward machine learning, generative AI, MLOps, and reliable AI application development.

The examples are learning exercises and are not intended as production-ready tools.