Generative AI for Finance: Applications & Responsible Use
10 AUGUST 2024 | 09:30AM - 05:30PM | RENAISSANCE :- Race Course Rd, Madhava Nagar Extension
About the workshop
Welcome to the cutting edge of financial innovation, where the intersection of artificial intelligence and finance is transforming the landscape of opportunity. In this workshop, "GenAI for Finance: Applications & Responsible Use," we invite you to explore the fusion of technological artistry with financial pragmatism. In this workshop, we will build GenAI-based applications to extract insights from financial reports—such as earnings and annual reports—enabling you to make more informed, data-driven investment decisions confidently. We will also build GenAI-based agents to connect to open-source APIs to extract financial data and create trading signals.
Through our immersive modules, you'll delve into the intricacies of Retrieval-Augmented Generation (RAGs) and AI Agents, learning to harness these tools skillfully to generate insights from financial documents. This journey, however, isn't solely about mastering technical skills; it's about striking a balance between innovation and responsibility. As we navigate the high-stakes realm of algorithm-driven decisions, it's crucial to approach these choices with care and ethical consideration. We'll also explore how to use language models responsibly while generating insights, ensuring that our advancements in AI are both effective and conscientious.
Instructor
Modules
In this module, we will create an application using RAGs and AI Agents to extract information from various financial documents, including SEC 10Q and 10K files, for a selection of financial securities within a specified universe. This information will then be used to generate trading signals.
Skills include:
- Creating a vector database
- Prompt engineering
- Building a retriever
- RAG and AI Agents
In this module we will create end to end LLMOps pipelines using langsmith to do prompt management, monitoring traces, automatic evaluation of the applications using benchmark datasets and or LLM as a judge etc.
Skills include:
- Prompt management
- Evaluation of the RAG pipeline
- Deploying the app on streamlit
This module focuses on the elements of Responsible AI within the finance industry. Considering the highly regulated nature of this sector, we will identify the challenges involved in deploying LLM applications and discuss strategies to overcome these issues.
Skills include:
- Hallucination
- Prompt injection
- PII detection
- Toxicity detection
- Bias detection
- Interpretation
We will learn open-source tools like langkit, guardrails to implement the above.
In this module, we will learn how to deploy and host the app using streamlit and get user feedback over time.
Skills/tools include:
- Streamlit
- Langsmith
- Intermediate Python programming skills
- Comfortable running Jupyter Notebooks using Anaconda/VS Code or Google Colab.
- Basic understanding of machine learning and natural language processing concepts
- Familiarity with financial concepts and terminology
- Experience with data analysis and manipulation
- Basic knowledge of API usage and web technologies
- Basic understanding of cloud computing platforms (e.g., AWS, GCP, or Azure)
- Familiarity with version control systems (e.g., Git)
Certificate of Participation
Receive a digital (blockchain-enabled) and physical certificate to showcase your accomplishment to the world
- Earn your certificate
- Share your achievement
