Fractal Data Science Professional Certificate Course Syllabus

Overview: This professional certificate program provides a comprehensive introduction to data science with a focus on practical, real-world applications in finance and business decision-making. Through a blend of quantitative modeling, data analysis, and visualization techniques, learners will develop the skills to build and interpret models that drive data-backed decisions. The program spans approximately 20-30 weeks of part-time study, with each module combining theory, hands-on exercises, and applied projects using Excel, SQL, Python, and Power BI.

Module 1: Fundamentals of Quantitative Modeling

Estimated time: 12 hours

• Introduction to quantitative models and their role in business
• Model design principles and best practices
• Mathematical and statistical foundations for modeling
• Interpreting model inputs, assumptions, and outputs

Module 2: Introduction to Spreadsheets and Models

Estimated time: 12 hours

• Excel fundamentals: cell referencing and formulas
• Conditional logic and data analysis in spreadsheets
• Building financial models for budgeting and forecasting
• Spreadsheet auditing, error detection, and versioning

Module 3: Modeling Risk and Realities

Estimated time: 18 hours

• Scenario and sensitivity analysis techniques
• Probabilistic modeling and risk quantification
• Monte Carlo simulations for risk assessment
• Identifying biases and limitations in financial models

Module 4: Decision-Making and Scenarios

Estimated time: 18 hours

• Applying models to strategic capital budgeting decisions
• Calculating and interpreting NPV and IRR
• Modeling financing structures and capital allocation
• Presenting scenario-based outcomes to stakeholders

Module 5: Data Analysis Using SQL and Python

Estimated time: 20 hours

• SQL for data extraction and manipulation
• Python basics for data science
• Data cleaning and transformation using Python
• Statistical analysis and predictive modeling in Python

Module 6: Data Visualization and Storytelling

Estimated time: 15 hours

• Data visualization principles with Power BI
• Creating interactive dashboards
• Communicating insights through data storytelling
• Influencing business decisions with visual summaries

Prerequisites

• Familiarity with basic spreadsheet software (e.g., Excel)
• Basic understanding of financial concepts (helpful but not required)
• High school level math and statistics knowledge

What You'll Be Able to Do After

• Build and validate quantitative models for business use
• Analyze large datasets using SQL and Python
• Assess financial risk using scenario and Monte Carlo analysis
• Create compelling data visualizations in Power BI
• Present data-driven narratives to support strategic decisions