Develop AI Champions Across Your Organization

Understand AI fundamentals, key tools, and applications in finance.

• Overview of AI, machine learning, and generative AI
• How to leverage AI chatbots in your own work
• Optional introduction to Claude Cowork, Anthropic's agent (requires a Claude subscription)

Learn Python to automate workflows and integrate AI.

• Python fundamentals for finance and business (no prior coding required)
• Integrating Excel and Python
• AI automation with APIs and business workflow enhancements
• Elective: Build AI-powered applications

Understand how GenAI models work and analyze complex data in Python.

• How generative AI works, and why it matters
• The pitfalls and limitations of large language models
• Analyzing large datasets in Python
• Data analysis with Pandas, Matplotlib, and more

Use linear models like regression to extract insights and make financial predictions.

• Linear & logistic regression, overfitting, and model validation
• Hedge fund strategies: Predicting stock returns & backtesting trading models
• Workforce analytics and dynamic pricing strategies

Use decision trees and random forests for complex financial predictions.

• Decision trees, random forests, and real-world applications
• Predicting loan defaults and early mortgage repayments
• AI-powered financial modeling

Apply simulation and optimization techniques to financial decision-making.

• Portfolio optimization, energy investment, workforce planning
• Understanding randomness in financial decisions
• Using simulation to quantify risk and optimization for large-scale decisions

Go deeper on embeddings and build AI tools for classification and fraud monitoring.

• Embeddings, the underlying language of LLMs
• Combining machine learning and generative AI with embeddings
• Multimodal embeddings across different kinds of data
• Classification systems for customer support using LLMs
• Fraud monitoring in financial payment networks with generative AI

Build your own AI agent and apply techniques like retrieval-augmented generation.

• The basics of agentic AI, and building your own AI agent
• Retrieval-augmented generation for financial analysis
• Predicting customer churn with AI-assisted entity resolution
• Automating financial data extraction for investment research