AI In Finance Course Syllabus

Overview: This course provides a practical introduction to artificial intelligence in the financial sector, designed for learners seeking to understand real-world AI applications in finance without deep technical prerequisites. The curriculum spans foundational computing concepts, neural networks, AI system design, natural language processing, computer vision, and deployment practices. With approximately 16-20 hours of content, learners engage through hands-on exercises, case studies, and guided projects that emphasize industry relevance. Ideal for those pursuing careers in fintech, analytics, or financial services, the course balances conceptual understanding with applied skills.

Module 1: Foundations of Computing & Algorithms

Estimated time: 3 hours

• Introduction to key concepts in foundations of computing & algorithms
• Hands-on exercises applying computing and algorithms techniques
• Discussion of best practices and industry standards

Module 2: Neural Networks & Deep Learning

Estimated time: 4 hours

• Review of tools and frameworks commonly used in practice
• Case study analysis with real-world examples
• Discussion of best practices and industry standards
• Assessment: Quiz and peer-reviewed assignment

Module 3: AI System Design & Architecture

Estimated time: 2 hours

• Hands-on exercises applying AI system design & architecture techniques
• Case study analysis with real-world examples
• Discussion of best practices and industry standards

Module 4: Natural Language Processing

Estimated time: 4 hours

• Discussion of best practices and industry standards
• Guided project work with instructor feedback
• Assessment: Quiz and peer-reviewed assignment

Module 5: Computer Vision & Pattern Recognition

Estimated time: 3 hours

• Introduction to key concepts in computer vision & pattern recognition
• Hands-on exercises applying computer vision & pattern recognition techniques
• Review of tools and frameworks commonly used in practice
• Discussion of best practices and industry standards

Module 6: Deployment & Production Systems

Estimated time: 2 hours

• Interactive lab: Building practical solutions
• Case study analysis with real-world examples
• Guided project work with instructor feedback
• Assessment: Quiz and peer-reviewed assignment

Prerequisites

• Familiarity with basic programming concepts
• Understanding of fundamental financial terminology
• Basic knowledge of data analysis principles

What You'll Be Able to Do After

• Implement intelligent systems using modern AI frameworks and libraries
• Evaluate model performance using appropriate metrics and benchmarks
• Apply computational thinking to solve complex financial engineering problems
• Design algorithms that scale efficiently with increasing financial data
• Build and deploy AI-powered applications for real-world finance use cases