AI In Finance Agent Course Syllabus

Full curriculum breakdown — modules, lessons, estimated time, and outcomes.

Overview: This course provides a practical introduction to AI agents in finance, designed for beginners with an interest in applying AI to financial workflows. Over approximately 16-21 hours of content, learners will progress through six modules covering core computing concepts, neural networks, AI system design, natural language processing, computer vision, and deployment practices. The course blends theory with hands-on projects and real-world case studies, preparing learners to implement AI solutions in financial contexts such as automation, analysis, and decision support.

Module 1: Foundations of Computing & Algorithms

Estimated time: 3 hours

Introduction to computational thinking
Algorithm design and analysis
Best practices in financial software development
Industry standards for AI in finance

Module 2: Neural Networks & Deep Learning

Estimated time: 4 hours

Core concepts of neural networks
Deep learning architectures
Transformer models and attention mechanisms
Tools and frameworks for deep learning in finance

Module 3: AI System Design & Architecture

Estimated time: 4 hours

Designing AI-powered financial systems
Case studies in AI agent integration
Best practices for scalable AI architectures
Evaluation of system performance

Module 4: Natural Language Processing

Estimated time: 2 hours

NLP fundamentals for financial text
Sentiment analysis in market data
Transformer-based language models
Applications in financial reporting and compliance

Module 5: Computer Vision & Pattern Recognition

Estimated time: 2 hours

Introduction to computer vision in finance
Pattern recognition for fraud detection
Visual data analysis in financial documents

Module 6: Deployment & Production Systems