Learning Portfolio: Data, AI, Engineering & DevOps

This repository documents my hands-on learning across data analytics, generative AI, machine learning, and DevOps. It is a working portfolio of notes, exercises, problem-solving practice, and small projects—not a collection of finished production systems.

My current goal is to build strong engineering foundations and apply them to data- and AI-focused work: working with data, building reliable software, and learning how to package and operate it.

Learning Focus

Data Analytics

I am building practical SQL and PostgreSQL skills for querying, cleaning, aggregating, and modeling data. The PostgreSQL work includes exercises using both a training database and the dvdrental sample database.

• Intro to PostgreSQL — querying, filtering, operators, NULL handling, aggregation, and HAVING.
• Mastering PostgreSQL — data types, constraints, advanced types, and indexing exercises.
• SQL practice materials

Generative AI & Machine Learning

I am developing the programming, mathematical, and data foundations needed for AI and machine-learning work. This repository currently includes an AI-agent learning module and foundational work in Python, algorithms, and mathematics; dedicated end-to-end ML projects will be added as that work progresses.

• Build an AI Agent
• Python foundations
• Mathematics notes
• Data Structures & Algorithms

DevOps & Systems

I am learning the tools and practices that support repeatable software delivery and reliable development environments, with an emphasis on Linux, Git, Docker, HTTP, and shell scripting.

• Linux
• Git
• Docker
• Bash Scripting Utility Lab

Supporting Engineering Practice

These areas strengthen the core skills behind my data, AI, and DevOps goals.

• Backend Developer Path — Python, TypeScript, SQL, HTTP, Docker, and backend architecture.
• LeetCode solutions — algorithmic problem solving in Python, JavaScript, TypeScript, and SQL.
• Personal projects — web applications, scripting utilities, and programming exercises.

Tools & Technologies

Languages: Python, SQL, JavaScript, TypeScript, Bash

Data: PostgreSQL

Engineering & DevOps: Linux, Git, Docker, HTTP, Node.js

Frontend projects: React, Vite, Tailwind CSS

Repository Structure

PS_SQL/    PostgreSQL courses, notes, and SQL practice
DSA/       Data structures and algorithms study material
leetcode/  Documented coding-challenge solutions
boot.dev/  Backend, systems, Docker, and AI-agent learning modules
projects/  Hands-on applications and utilities

Direction

I am actively expanding this portfolio toward data-analysis workflows, machine-learning projects, generative-AI applications, and containerized deployments. Each addition is intended to show both what I am learning and how I apply it in code.