This repo contains all the solutions to my projects as they pertain to the Udacity Nanodegrees that make up the MS AI.
This may serve as inspiration to fellow learners, but please be sure to follow the Udacity Honor Code and reference any borrowed material.
Data cleaning, PostgreSQL, MongoDB, Database normalization, Database schemas, Database manipulation language (DML), SQL query performance tuning, SQL subqueries, SQL window functions
P1: A Data-Driven Approach to AI and Python
High-level goal: Set up a data science environment, manipulate and visualize data, transform and export cleaned datasets for machine learning model training, and generate insightful visualizations and summaries to help the business team identify top-performing products in the electronics category
Technologies used: Python, pandas, Matplotlib, Seaborn
High-level goal: Explore deforestation datasets with relational queries to surface trends and comparisons.
Technologies used: SQL querying, joins and aggregations, result interpretation, and basic visualization exports.
P2: Udiddit, A Social News Aggregator
High-level goal: Normalize a flawed forum database, migrate existing data, and validate integrity at scale.
Technologies used: PostgreSQL DDL/DML/DQL, indexes and constraints, Dockerized Postgres 15 workflow, validation queries, and expected counts.