Complete coursework from Western Governors University's Master of Science in Data Analytics — SQL, Python, R, Tableau, machine learning, and a full data science capstone. Every project is linked.
An interactive AI/BI dashboard built in Python and deployed on Streamlit — not a screenshot, not a mockup. Click through and explore.
Every project below links to the actual deliverable on GitHub — PDFs, notebooks, and code files from the WGU Master of Science in Data Analytics program.
Foundation course on the data analytics lifecycle, career planning, and problem-framing methodology. Two tasks linked.
Advanced database design covering relational (SQL) and non-relational (NoSQL) systems, ERDs, and query optimization.
Python programming for data analytics — data structures, pandas, NumPy, and scripting for data pipelines.
Data wrangling, cleaning, EDA, and feature engineering using Python — from raw ingestion to analysis-ready datasets.
Statistical modeling and data mining techniques — regression, clustering, decision trees, and model evaluation in Python.
Designing and building Tableau dashboards that communicate insights clearly to non-technical stakeholders. Narrative-driven viz.
Deploying machine learning models and data applications — REST APIs, containerization concepts, and production-readiness.
Supervised and unsupervised machine learning — model selection, training, evaluation, and bias-variance tradeoff in Python.
Deep learning fundamentals, time-series forecasting, and neural network architectures applied to real business datasets.
Linear programming, constraint-based optimization, and simulation — using Python to model and solve real-world resource allocation problems.
Full-cycle data science capstone in R — problem framing, data collection, analysis, modeling, and final report with stakeholder presentation.
Percentages reflect applied comfort across real projects — not self-reported guesses.
Browse all 11 WGU courses, fork anything useful, and follow along as new work ships.