ADVANCED HEALTHCARE ANALYTICS

• What SQL does well: filtering, grouping, joining healthcare data
• Mapping common healthcare questions to tables & joins
• SQL → Python → Tableau workflow
• Limits of SQL for modeling & scenario analysis

• Core healthcare entities: patient, encounter, event, time
• Fragmented & messy healthcare data
• Translating operational questions into data structures
• Reading a data dictionary at a high level

• Problems SQL & dashboards cannot solve
• Python for prediction, simulation, scenario testing
• How Python complements SQL & Tableau
• What “coding” means for analysts

• Python notebook for analysts 
• Core concepts: variables, functions, DataFrames
• Exploring data in Python
• Interpreting errors & outputs at a high level

Get set up and ready to roll. In this session, you’ll meet your instructor, test-drive the tools, and get a clear picture of what’s ahead. Think of it as your pre-flight check before diving into the data.

• Instructor intro & support channels
• Cloud environment check-in (BigQuery project + Colab)
• Syllabus & assessments walkthrough with Q&A 

Get a clear view of how analytics moves the needle in healthcare. See where data fits into real-world decision-making, what kinds of healthcare data matter, and how to spot the opportunities where analytics can truly make an impact.

• Analytics maturity model & how organizations progress through it
• Identifying problems to solve in healthcare
• Common healthcare data types: Clinical, operational, financial
• Real-world applications of analytics in healthcare delivery & operations

Explore where advanced analytics makes the biggest impact and the toughest calls. You’ll weigh high-value healthcare use cases against the ethical risks they carry, from bias to behavior modeling, and look ahead to what responsible innovation actually looks like in practice.

• Ethical implications of advanced analytics in healthcare: Bias & fairness
• The future & impact of advanced analytics in healthcare 
• Workshop: Modeling behavioral decontrol as a high-value, high-risk problem

Get fluent in SQL — the language behind every great healthcare insight. Dive into real datasets in BigQuery, learn how data is structured, and start writing queries that mean something. Less theory, more doing.

• SQL: Why it matters for healthcare analysts
• Intro to BigQuery healthcare datasets: Structure
• SQL statement basics with Gen AI for faster learning & practice

Learn how to make your data do the heavy lifting. This session shows you how to design clean, reusable datasets that answer complex healthcare questions again and again — no more reinventing the wheel with every new query.

• Designing analyst-ready datasets in healthcare
• Building structures to answer questions consistently 
• Using SQL for efficiency & reducing rework

Let AI write your SQL without losing control of your data. This class shows you how to prompt effectively, validate results, and build safety checks that keep your healthcare analytics reliable, compliant, and human-approved.

• Prompting for accurate SQL 
• Workflows for validation & error-checking
• Safety rails & human-in-the-loop practices

Get comfortable with Python — the go-to tool for turning messy healthcare data into clear, actionable insights. You’ll learn when to ditch spreadsheets, how to clean and analyze data efficiently, and what makes Python the analyst’s secret weapon in healthcare.

• Using Python vs. other tools
• Basic use cases: Accessing, transforming, calculating data
• Statistical tests & row-by-row processes
• Profiling data to assess distributions, missingness, & quality

Get hands-on with predictive modeling — from setting up your first models to making sure they hold up under pressure. You’ll experiment, tune, and test without falling into the overfitting trap.

• Exploring candidate models to find best-fit approaches
• Scikit-learn basics: Train/test splits
• Hyperparameter tuning without overfitting

See what happens when predictions meet the real world. Learn how to measure the actual impact of your models on healthcare decisions — and compare them to simpler rules, older systems, or even doing nothing at all. Plus, explore how generative AI can reshape the way we frame predictions in the first place.

• Measuring real decision impact of predictive models
• Benchmarking against naïve rules, existing models, or doing nothing
• Using generative AI for prediction framing

Get inside the engine of healthcare. Use systems thinking to map how patients, data, and decisions move through a hospital and see how one small bottleneck can ripple through the entire system.

• Systems thinking & cognitive engineering
• Patient flow, capacity, demand modeling
• Conceptual vs. predictive modeling
• Workshop: Mapping a patient journey from admission to discharge

Get comfortable with uncertainty. Use simulation to test how systems behave when life or data gets messy. You’ll experiment with Monte Carlo, discrete-event, and agent-based models to see what really happens behind the numbers.

• Monte Carlo simulation for uncertainty
• Discrete-event simulation: Queues, arrivals, service times
• Agent-based simulation for human interactions
• Case Study: ED triage queue model

Learn how to make tough choices smarter. Explore how optimization helps balance resources, staffing, and scheduling in healthcare, finding the sweet spot between efficiency, cost, and care quality.

• Optimization vs. prediction & simulation
• Workflow: Goal definition, constraints, levers, optimization runs
• Methods: Linear programming, integer programming, heuristics
• Healthcare examples: Staffing, scheduling, resource allocation

Assignment #2: Simulating Stress Scenarios & Optimizing Interventions for Hospital Capacity 

Turn healthcare data into dashboards that tell a story. Learn how to build clean, decision-ready visuals in Tableau — the kind that busy leaders can understand at a glance and actually use.

• Principles of effective visualization in healthcare
• Connecting Tableau to healthcare datasets
• Building core chart types: Bar, line, scatter, tree maps
• Designing dashboards for operational & predictive use
• AI-assisted Tableau for efficiency

Translate analytics into executive-level stories. Learn how to shape your numbers into narratives executives care about — clear, credible, and built to drive action.

• Narrative arcs from raw data to compelling story
• Storytelling frameworks for healthcare audiences
• Dashboards as storytelling tools
• Ensuring reproducibility & trust in analytics

Final Project: Stress-Testing Surgical Ramp-Up Strategies