Course

Credit Type:
Course
ACE ID:
SKUP-0003
Version:
1
Organization:
SkillUp Technologies
Location:
Online
Length:
30 hours
Minimum Passing Score:
80
ACE Credit Recommendation Period:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Upper-Division Baccalaureate 3 Financial Analysis
Upper-Division Baccalaureate 2 AI Labs for Financial Analysis
Description

Objective:

The course objective is to introduce financial workers, students and instructors to the practical application of artificial intelligence in modern financial analysis. The course develops essential skills for using AI tools to research and interpret financial statements, earnings information, company and market intelligence, alternative data, and financial performance. Students learn to create effective prompts, generate professional financial narratives, and develop repeatable AI-assisted workflows, all without requiring coding experience. Through hands-on labs, financial scenarios, prompt-engineering exercises, collaborative activities, and a capstone project, students learn to apply AI to realistic financial tasks while developing the critical judgment needed to evaluate AI-generated results for accuracy, bias, completeness, ethics, and compliance.

Learning Outcomes:

  • Use AI tools to extract, summarize, and interpret financial statements, filings, and earnings materials.
  • Analyze company, sector, and market intelligence using AI-assisted workflows.
  • Generate structured financial narratives (research notes, summaries, reports) using prompt engineering techniques.
  • Compare financial performance across companies and periods using AI-driven analysis.
  • Apply AI to alternative data sources to identify emerging trends and thematic insights.
  • Develop repeatable workflows for research, reporting, and stakeholder communication.
  • Evaluate AI-generated outputs for accuracy, bias, and completeness before dissemination.
  • Design and maintain prompt libraries and documented workflows for team-wide use.
  • Demonstrate compliance with regulatory, ethical, and information barrier requirements when using AI.
  • Construct an AI-powered financial analysis workflow suitable for individual or team deployment.

General Topics:

  • AI Tools for Every Analyst
  • AI for Financial Statement Reading and KPI Extraction
  • Earnings Intelligence and Transcript Analysis
  • Market and Sector Intelligence with AI
  • Data Interpretation Without Code
  • AI-Driven Equity Research Workflows
  • Credit Analysis and Fixed Income Intelligence
  • Alternative Data and Thematic Research with AI
  • Internal Reporting and Stakeholder Communication with AI
  • Prompt Library Design and Workflow Documentation
  • Client-Facing Content Generation and Senior Review
  • Portfolio Analytics and Senior-Level AI Workflows
  • AI Ethics, Information Barriers and Regulatory Compliance
  • Multimodal AI and Advanced Research Techniques
  • Design Your AI-Powered Analysis Workflow
Instruction & Assessment

Instructional Strategies:

  • Audio Visual Materials
  • Case Studies
  • Discussion
  • Laboratory
  • Practical Exercises
  • Work-based Learning

Methods of Assessment:

  • Other
  • Performance Rubrics (Checklists)
  • Quizzes
  • Hands-on Labs
Supplemental Materials
Equivalencies

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