This course introduces learners to the integration of artificial intelligence and machine learning in modern financial analysis. It explores automated data extraction, pattern recognition, anomaly detection, forecasting models, and AI-driven decision support tools. Students learn how advanced technologies enhance analytical accuracy, speed, and insight in today’s data-rich financial landscape. Designed for analysts and forward-thinking professionals, the course prepares learners to apply AI techniques to real-world financial evaluation and reporting.

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Skills & learning objectives

There are 7 modules in this class


  • Overview of AI and Machine LearningUnlock this class to watch2m 18s
  • Key Concepts of AIUnlock this class to watch2m 11s
  • Key Concepts of MLUnlock this class to watch2m 6s
  • Applications of AI and ML in FinanceUnlock this class to watch6m 34s
  • The Role of AI in Financial AnalysisUnlock this class to watch6m 5s
  • Future Potential of AI in FinanceUnlock this class to watch3m 6s
  • AI SubfieldsUnlock this class to watch9m 23s
  • Challenges of Incorporating AI into Finacial AnalysisUnlock this class to watch1m 57s

  • Review of key financial statements and conceptsUnlock this class to watch8m 20s
  • Financial ratios and metricsUnlock this class to watch5m 30s
  • Traditional Financial Analysis TechniquesUnlock this class to watch4m 54s
  • Using AI for automated ratio calculationsUnlock this class to watch3m 45s

  • Vertical AnalysisUnlock this class to watch5m 35s
  • Horizontal AnalysisUnlock this class to watch2m 57s
  • Machine Learning in Financial AnalysisUnlock this class to watch1m 58s
  • Deep Learning in Financial AnalysisUnlock this class to watch5m 27s
  • Natural Language Processing in Financial AnalysisUnlock this class to watch6m 5s

  • Data Gathering and ProcessingUnlock this class to watch3m 6s
  • Integration of Structured and Unstructured DataUnlock this class to watch1m 45s
  • Finacial Modeling and ForecastingUnlock this class to watch2m 45s
  • AI in Risk Assessment and ManagementUnlock this class to watch2m 32s
  • Ai in Fraud DetectionUnlock this class to watch2m 47s
  • AI in Investment ManagementUnlock this class to watch5m 19s
  • AI in Trading strategiesUnlock this class to watch2m 26s
  • Challenges and Ethical Considerations in AI-Enhanced Financial AnalysisUnlock this class to watch1m 51s

  • Overview of Popular AI Tools in FinanceUnlock this class to watch3m 12s
  • AI-Powerd Financial Analysis WorkflowsUnlock this class to watch5m 56s

  • Advancements in AI and M achine LearningUnlock this class to watch7m 49s
  • Reinforcement LearningUnlock this class to watch4m 32s
  • Generative AIUnlock this class to watch7m 50s
  • Integration with Other TechnologiesUnlock this class to watch25m 7s
  • ClosingUnlock this class to watch1m

Final exam

Assess your learning with a final exam covering all class topics.

This class is part of the following certifications

Issued by Capital Academy and the American University in Dubai (AUD)
Certified Portfolio & Fund Manager (CPFM)

Certified Portfolio & Fund Manager (CPFM)

63 ClassesUnlimited interactive exercises

Unlock Certificate
Issued by Capital Academy and the American University in Dubai (AUD)
Certificate in AI-Powered Financial Analysis (CAFA)

Certificate in AI-Powered Financial Analysis (CAFA)

56 ClassesUnlimited interactive exercises

Unlock Certificate

ClassFAQs

The course aims to equip learners with the knowledge and skills to apply Artificial Intelligence and Machine Learning tools to improve financial analysis, forecasting, automation, and decision-making.
The course is designed for finance professionals and analysts seeking to integrate AI-powered tools into financial modeling, risk assessment, and performance evaluation.
The module introduces the fundamentals of AI and Machine Learning and explores their impact on financial areas such as algorithmic trading, fraud detection, risk management, and customer service.
The course demonstrates how AI improves data gathering, processing, modeling, forecasting, and risk assessment, while addressing challenges like data integration and anomaly detection.
Learners explore emerging technologies such as Quantum Computing, IoT integration, and Generative AI, and evaluate how they will shape the future of financial services.

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