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Caboto Sim S

Master Financial Analysis with AI

Build expertise in automated financial reporting through hands-on learning and real-world applications

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Your Learning Path

We've designed a progressive curriculum that takes you from foundational concepts to advanced AI-driven financial analysis

Students engaged in financial analysis training
1

Financial Fundamentals

Master core accounting principles and financial statement analysis. You'll work with real company data to understand balance sheets, income statements, and cash flow patterns.

Duration: 6 weeks | Skills: Financial ratio analysis, trend identification

2

Data Processing & Automation

Learn how to clean, organize, and prepare financial data for automated analysis. We focus on practical techniques you'll use every day.

Duration: 4 weeks | Skills: Data validation, error detection, process automation

3

AI Report Generation

Discover how AI transforms raw data into professional reports. You'll create comprehensive financial analyses that would typically take days to complete manually.

Duration: 8 weeks | Skills: Report customization, insight extraction, quality control

Flexible Learning That Fits Your Schedule

Everyone learns differently, and your professional commitments vary. That's why we've created multiple ways to engage with the material, whether you prefer intensive workshops or self-paced study.

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Live Sessions

Interactive workshops every Tuesday and Thursday evening, with expert instructors available for immediate feedback

S

Self-Paced

Complete modules on your timeline with recorded lectures and practice exercises available 24/7

M

Mentoring

One-on-one guidance sessions to address your specific learning needs and career objectives

P

Projects

Real client work supervised by industry professionals, giving you portfolio-ready experience

Professional working on financial analysis with multiple learning resources

Common Challenges We Address

Based on feedback from over 400 professionals, we've identified the most frequent obstacles and developed specific solutions

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Data Quality Issues

Many students struggle with inconsistent data formats and missing information that makes automation difficult.

We teach systematic data cleaning approaches and provide templates for common scenarios. You'll practice with messy real-world datasets until data preparation becomes automatic.

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Technical Complexity

The intersection of finance and technology can feel overwhelming, especially for professionals with strong financial backgrounds but limited tech experience.

Our curriculum introduces technical concepts gradually, always connecting them to financial applications you already understand. No programming experience required.

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AI Output Validation

Knowing when AI-generated reports are accurate versus when they need human review is a critical skill that many programs don't address.

We dedicate significant time to teaching quality control methods. You'll learn to spot common AI errors and develop systematic review processes that ensure report reliability.

Learn from Industry Experts

Our instructors combine deep financial expertise with practical AI implementation experience from leading European financial institutions

Instructor Marco Bellacorte

Marco Bellacorte

Senior Financial Analyst

Former risk management director at UniCredit with 15 years implementing automated reporting systems. Marco specializes in helping professionals transition from manual to AI-assisted analysis.

Instructor Elena Rossetti

Elena Rossetti

AI Systems Specialist

Built AI integration systems for three major Italian banks. Elena makes complex technology accessible and teaches practical implementation strategies that actually work in corporate environments.

Instructor Giuseppe Romano

Giuseppe Romano

Financial Technology Consultant

Advises mid-size companies on financial process optimization. Giuseppe brings real client challenges into the classroom and helps students understand business impact beyond technical skills.

Ready to Transform Your Financial Analysis Skills?

Next cohort begins September 2025 with early application deadline in June

Limited to 24 participants to ensure personalized attention and meaningful interaction

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