Note - SPPU's Degreeplus Beta Version is up, stay tuned for more details.
Note - SPPU's Degreeplus Beta Version is up, stay tuned for more details.

Course

AI for Finance Professionals

17 hours 26 minutes

Credits: Optional Learning

Description

In this course, learners will develop practical AI skills tailored to the financial services profession – from understanding generative AI and responsible use principles through to applying prompt engineering, evaluating AI outputs, and executing AI-powered financial workflows. Learners will explore AI in the workplace, responsible AI practices, and AI applications specific to financial planning and analysis. They will develop structured prompt engineering skills through interactive courses and hands-on labs, and critically evaluate AI outputs by identifying pitfalls, biases, risks, and limitations of large language models. Through a series of finance-specific generative AI labs, learners will apply AI to real-world scenarios including investment banking pitch building, investor relations, mergers and acquisitions, risk and compliance, valuation, and venture capital screening. The course concludes with AI change management strategies to help financial professionals lead their teams through AI-driven transformation and build a culture of continuous learning.

What Students Will Learn

  • Introduction to Generative AI
  • AI in the Workplace
  • Responsible Use of AI
  • Considerations for Using AI Responsibly
  • AI for Financial Planning and Analysis Skillshort

  • Introduction to Prompt Engineering
  • Crafting Effective Prompts
  • Prompt Engineering Lab: Crafting Effective Prompts
  • Prompt Engineering Techniques

  • Generative AI Pitfalls
  • Risks and Limitations of ChatGPT
  • AI Model Auditing and the Future
  • LLM Bias, Fairness, and Ethical Considerations
  • Leveraging Analytical and Critical Thinking to Implement AI
  • Managing the Responsible Use of AI
  • Leveraging AI in Decision-Making

  • Generative AI Finance Lab: Investment Banking Pitch Builder
  • Generative AI Finance Lab: Investor Relations Communications Review
  • Generative AI Finance Lab: Mergers & Acquisitions Deal Memo
  • Generative AI Finance Lab: Risk and Compliance Decision Lab
  • Generative AI Finance Lab: Valuation & Fairness Opinion Assistant
  • Generative AI Finance Lab: Venture Capital & Private Equity Screening
  • Investing in AI: Business and Capital Landscape Skillshort

  • AI Change Management: Understanding Drivers and Impact
  • AI Change Management: Leading the Transformation
  • AI Change Management: Cultivating a Continuous Learning Culture
  • Change Management in the Age of AI: Leading Your Team to Success

  • Intermediate Prompt Engineering Techniques Cheatsheet
  • Crafting Effective Prompts Cheatsheet
  • AI for Financial Planning and Analysis Skillshort Cheatsheet
  • Generative AI Pitfalls Cheatsheet
  • Introduction to Generative AI Cheatsheet
  • Investing in AI: Business and Capital Landscape Skillshort Cheatsheet
  • Prompt Engineering with Generative AI Cheatsheet

Overall Learning Outcomes

  • Explain generative AI concepts and describe how AI is being applied in workplace and financial contexts
  • Apply responsible AI principles and evaluate the ethical implications of AI use in professional environments
  • Engineer effective prompts using structured techniques to improve the quality and reliability of AI outputs
  • Identify and assess generative AI pitfalls, risks, LLM biases, and fairness considerations
  • Apply analytical and critical thinking to evaluate AI-generated outputs and support sound decision-making
  • Use generative AI tools to complete real-world financial tasks including pitch building, M&A memos, valuation, compliance decisions, and investor communications
  • Assess the AI investment landscape and understand the business and capital implications of AI adoption
  • Lead AI change management initiatives by understanding transformation drivers, guiding teams, and cultivating a continuous learning culture