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There is 1 module in this course
This course offers a practical exploration of Generative AI (GEN AI) and its transformative applications in financial data analysis. By examining real-world use cases and utilizing AI tools like Microsoft Co-Pilot, ChatGPT, Datarobot, and Chartpixel, participants will learn to extract actionable insights from financial datasets. The course emphasizes hands-on learning, enabling learners to build custom AI solutions using open-source models while adhering to ethical considerations.
This course is designed to take learners with a basic understanding of financial data and AI concepts to the next level, focusing on practical applications of Generative AI (GEN AI) in financial data analysis. You’ll dive deep into specific use cases, learning how to use AI tools to extract actionable insights from financial data. We’ll demonstrate AI tools in action, showing how to optimize financial strategies through data analysis, all while highlighting the best practices to maximize GEN AI’s potential in finance.
Learners should have a basic understanding of financial analysis and AI/machine learning concepts, as well as familiarity with data handling and statistical methods.
By the end of this course, learners will be able to use GenAI tools to extract actionable insights from large datasets, optimize data-driven decision making and develop innovate solutions for complex data challenges.
This course is designed to take learners with a basic understanding of financial data and AI concepts to the next level, focusing on practical applications of Generative AI (GEN AI) in financial data analysis. You’ll dive deep into specific use cases, learning how to use AI tools to extract actionable insights from financial data. We’ll demonstrate AI tools in action, showing how to optimize financial strategies through data analysis, all while highlighting the best practices to maximize GEN AI’s potential in finance.
What's included
13 videos4 readings4 assignments
Show info about module content
13 videos•Total 89 minutes
Introduction to the Course & Meet Your Instructor•2 minutes
Understanding GEN AI and Its Financial Applications•7 minutes
Create Prompts for Data Analysis (Demonstration Using ChatGPT)•7 minutes
Make your Toolkit for Data Analysis and Visualization•9 minutes
Demonstration of General AI Models Capabilities•13 minutes
Demonstration of Custom Tools for Data Analysis•5 minutes
DataRobot: Account Setup, Data Wrangling, & Model Deployment•11 minutes
Demonstration of Microsoft Copilot Capabilities for Data Analysis•5 minutes
How to Use Data Visualization Tools for Analysis•7 minutes
Overcoming Challenges in GEN AI Implementation•7 minutes
Best Practices for Maximizing GEN AI Efficiency in Finance•5 minutes
Building Custom AI Tools with Open-Source Models•10 minutes
Congratulations and Continuous Learning Journey•1 minute
4 readings•Total 20 minutes
Welcome to the Course: Course Overview•5 minutes
Financial Data Analysis Framework•5 minutes
Top 10 Tools for Data Analysis for Experts and Beginners•5 minutes
Using Generative AI To Get Insights from Disorderly Data•5 minutes
4 assignments•Total 110 minutes
Chain of Thought Prompt Development for Financial Statement Analysis•15 minutes
Detailed Analysis of Court Booking Data•30 minutes
Custom AI Tool for Court Booking Data Analysis•45 minutes
GenAI for Financial Data Analysis•20 minutes
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What does using GenAI for financial data analysis mean in this course?
In this course, using GenAI for financial data analysis means guiding generative AI tools to examine financial data, surface patterns, and produce usable analysis in plain language. The emphasis is on practical analysis work such as asking better questions, interpreting outputs, and using AI responsibly in finance.
When would you use this GenAI approach to financial analysis?
You would use this approach when you need help exploring financial data, summarizing findings, or working through a specific analysis question with AI support. The course treats it as most useful when you want a repeatable way to move from a business question to actionable insights rather than relying on isolated prompts.
How does this GenAI approach fit into a broader workflow?
It fits into the middle of the analysis process, after you understand the financial question and as you begin exploring data, testing interpretations, and shaping recommendations. In the course, GenAI supports those connected analysis steps alongside tool selection, data handling, and output review.
How is this GenAI approach to financial analysis different from using AI for one-off answers?
In this course, GenAI is used as a guided analysis process, not just a way to ask a chatbot for a single answer. Learners focus on setting objectives, refining prompts, checking outputs, and choosing tools that fit the financial task.
Do you need any prerequisites before learning this GenAI approach to financial analysis?
A basic understanding of financial analysis, AI or machine learning concepts, data handling, and statistical methods is helpful before starting. The course is beginner level, but it assumes you can follow financial data and basic analytical reasoning.
What tools, platforms, or methods are used in this course?
Learners work with conversational AI tools such as ChatGPT and Microsoft Copilot, along with other tools for data management and visualization. Prompt engineering and building custom solutions with open-source models are two of the main methods covered.
What specific tasks will you practice or complete in this course?
You practice framing analysis questions, writing and refining prompts, using AI tools to extract insights from financial data, and creating report or visualization-ready outputs. You also evaluate which tools fit a use case and work through data quality, ethics, and customization issues that affect GenAI analysis in finance.