“Mastering LangChain and AWS” is a project-focused course designed to guide learners through the essentials of building AI-driven applications. By introducing LangChain’s core capabilities, SQL integration, and AWS deployment strategies, the course offers a structured pathway to create robust, data-centric LLM applications in the financial domain and beyond.
Curriculum Design
The course opens with environment setup, including Python, Jupyter notebooks, and relevant libraries (e.g., pandas_datareader, sqlite3, openai, langchain). Modules advance from basic LangChain concepts—like prompt templates and simple queries—to more advanced agent features, including memory management, custom tools, and retrieval-based QA.
Data and Practical Demonstrations
Real-world economic datasets from FRED (Federal Reserve Economic Data) are used to populate SQLite databases, showcasing how to handle yield curves, unemployment rates, industrial production, and business cycles. Step-by-step Jupyter notebooks illustrate data ingestion, schema creation, SQL querying, and natural language interaction with the data via LangChain.
AWS Integration
Learners receive guidance on integrating AI models with AWS services, emphasizing deployment considerations and scalability. Tutorials highlight best practices for configuring AWS resources to run LangChain applications in production-like settings.
Comprehensive AI Skillset
Students gain proficiency in creating AI agents capable of conversing with structured SQL data, leveraging prompt engineering, and implementing advanced features such as date-formatting tools and custom memory backends.
Financial Data Analysis Use Cases
The course’s focus on economic and financial data empowers learners to apply AI solutions to real-world scenarios—such as analyzing yield curve trends or forecasting economic indicators—using natural language queries.
Deployment Readiness
Through AWS-focused sections, participants understand how to scale and manage AI workloads, ensuring that LangChain applications can transition smoothly from development to production.
