Foundations of Deep Learning
Spring 2026 · Grade: A
Topics covered: neural networks, log loss, binary classification, hidden layers, predictions, convolutional neural networks
- Built foundations in how neural architectures transform inputs into predictions.
- Analyzed binary classification behavior with log-loss driven model evaluation.
Deep LearningNeural NetsClassificationCNN
Math for Data Science
Fall 2025 · Grade: A
Topics covered: linear regression, logistic regression, random forest, recall, gradient descent, MSE
- Modeled predictive problems across linear and non-linear approaches.
- Interpreted model quality using recall and error-based evaluation metrics.
RegressionRandom ForestGradient DescentMetrics
Business Analytics
Spring 2025 · Grade: A
Topics covered: advanced statistics, predictive models, warehouse capacity modeling, price modeling, probability theory, normal distribution
- Applied predictive modeling to operational and pricing decisions.
- Worked with probability distributions to evaluate uncertainty in business planning.
Predictive ModelsStatisticsProbabilityAnalytics
Relational Databases
Spring 2026 · Grade: A
Topics covered: SQL, database creation, building AI applications from databases, SQLModel, FastAPI
- Designed relational structures and queried data with production-style SQL workflows.
- Connected database layers to modern AI application backends using SQLModel and FastAPI.
SQLFastAPISQLModelDatabases
Big Data Analytics
Spring 2026 · Grade: A
Topics covered: large dataset workflows, preprocessing, cleaning, hypothesis development, hypothesis testing, Spark
- Worked with large-scale datasets and structured preprocessing pipelines.
- Combined hypothesis development and testing with distributed analytics tools.
SparkBig DataHypothesis TestingPreprocessing
Intro to Data Science
Fall 2024 · Grade: A
Topics covered: R, data cleaning, data visualization, data interpretation, communicating insights
- Covered the full analysis workflow from raw data to clear decision-ready outputs.
- Built foundations in communicating analytical findings with concise visual narratives.
RData CleaningVisualizationInsights
Data Visualization and Communication
Spring 2026 · Grade: A
Topics covered: Power BI, chart selection, visual clarity, communicating insights effectively
- Designed visuals to match analytical intent and audience decision needs.
- Interpreted results through concise chart-first communication in Power BI.
Power BIData VizStorytelling
Marketing Research
Fall 2025 · Grade: A
Topics covered: SPSS, research design, selecting statistical tests, when and why to use different tests, communicating results
- Analyzed research questions by matching them to appropriate statistical methods.
- Worked with SPSS to produce clear, decision-oriented research outputs.
SPSSResearch DesignStatistical TestsInsights
Linear Data Structures
Spring 2025 · Grade: A
Topics covered: Python-based data structures and programming progression from Intro to Computer Science
- Applied structured problem-solving with core linear data structures.
- Strengthened Python fluency through progressively complex implementations.
PythonData StructuresProgramming
Non-Linear Data Structures
Fall 2025 · Grade: A
Topics covered: continued Python progression through non-linear data structures and advanced programming patterns
- Extended core programming foundations into non-linear structure design and analysis.
- Modeled computational tradeoffs with more complex algorithmic patterns.
PythonData StructuresAlgorithmsProgramming
Intro to Computer Science
Fall 2024 · Grade: A
Topics covered: foundational programming in Python
- Built foundations in computational thinking and code structure.
- Applied Python to solve structured analytical and logical tasks.
PythonProgramming
Intro to Statistics
Spring 2024 · Grade: A
Topics covered: probability theory, normal distribution, empirical rule, proportions, charts and graphs, t-tests
- Built statistical foundations for interpreting variability, distributions, and inference.
- Analyzed proportions and hypothesis tests to support evidence-based conclusions.
StatisticsProbabilityT-TestsData Interpretation
Managerial Economics
Fall 2025 · Grade: A
Topics covered: advanced economics for business decision-making
- Applied economic reasoning to managerial tradeoffs and strategic choices.
- Interpreted market and cost signals in practical business contexts.
EconomicsDecision-MakingBusiness
Financial Management
Fall 2025 · Grade: A
Topics covered: finance principles, financial analysis, and business decision-making
- Analyzed financial information to support planning and investment choices.
- Covered core frameworks used in managerial finance decisions.
FinanceAnalysisDecision-Making
Microeconomics
Spring 2025 · Grade: A
Topics covered: applied economics for business decision-making
- Modeled firm and consumer behavior in decision-focused scenarios.
- Interpreted market signals and incentives in applied business contexts.
EconomicsMarket AnalysisBusiness
Macroeconomics
Fall 2024 · Grade: A
Topics covered: macroeconomic and business foundations
- Covered aggregate indicators that shape business environments.
- Analyzed how macro trends influence strategic planning decisions.
EconomicsMacroBusiness
Accounting
Fall 2024 · Grade: A
Topics covered: foundational accounting concepts
- Built foundations in financial statements and accounting logic.
- Interpreted accounting information in a business decision context.
AccountingFinancial StatementsBusiness
Accounting II
Spring 2025 · Grade: A
Topics covered: advanced accounting concepts in a second-course progression
- Extended foundational accounting into more advanced treatment of financial topics.
- Applied accounting analysis to evaluate business performance and decisions.
AccountingFinanceAnalysis
Digital Marketing
Spring 2025 · Grade: A
Topics covered: digital marketing strategy and applied marketing execution
- Covered digital channel strategy with execution-oriented planning.
- Analyzed campaign structure through a business outcomes lens.
MarketingDigital StrategyExecution
Social Media Marketing
Fall 2024 · Grade: A
Topics covered: social media marketing strategy and execution
- Covered channel-specific planning and practical social strategy choices.
- Interpreted how content and execution decisions support brand and growth goals.
MarketingSocial MediaStrategy