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Python & Financial Software DevelopmentEnrollment opening soon

Building Financial Dashboards & Applications

Design and build interactive financial dashboards and small web applications with Python, from data layer and charts to authentication, testing and deployment.

  • Duration7 weeks
  • LevelIntermediate
  • Modules7
  • Lessons28
Enroll nowView curriculum
Building Financial Dashboards & Applications
Proposed fee$899USD · 7 weeks

Course overview

This course takes you from analysis scripts to usable financial applications. You will design dashboards that present prices, portfolios and risk metrics clearly, build them with Python dashboard frameworks and a FastAPI backend, and add interactivity, caching and user authentication. The final weeks cover testing, containerized deployment and the design choices that keep financial interfaces accurate, accessible and free of misleading visuals.

  • Dashboard design principles
  • Interactive charting
  • Application data layer
  • FastAPI backends
  • Authentication and security
  • Testing and deployment

What you will learn

  • Apply information design principles to present prices, portfolio data and risk metrics without distortion
  • Build interactive dashboards with Plotly, Dash or Streamlit backed by a clean data access layer
  • Develop a FastAPI backend that serves analytics endpoints with validation and caching
  • Add user authentication, role-based access and secure configuration to a financial application
  • Test, containerize and deploy an application with monitoring and documented operations

Curriculum

7 modules · 28 lessons · 7 weeks. Curriculum preview; the final syllabus may change before enrollment opens.

  • Who uses financial dashboards and what they need
  • Choosing the right chart for prices, returns and risk
  • Avoiding misleading scales, colors and baselines
  • Wireframing and layout planning

  • Plotly fundamentals: candlesticks, lines and heatmaps
  • Subplots, annotations and range selectors
  • Performance with large time series
  • Accessible color palettes and labeling

  • Rapid prototyping with Streamlit
  • Dash layouts and callbacks
  • State management and user inputs
  • Multi-page application structure

  • Separating data access from presentation
  • Querying PostgreSQL efficiently for dashboards
  • Caching strategies and refresh schedules
  • Handling missing and delayed data in the UI

  • Designing analytics endpoints
  • Pydantic models and input validation
  • Background tasks and scheduled computations
  • Connecting dashboards to the API

  • Authentication options and session handling
  • Role-based access to data and features
  • Secrets, configuration and environment separation
  • Audit logging and clear disclaimers in the UI

  • Unit and end-to-end tests for dashboards
  • Containerizing the app with Docker Compose
  • Deploying to a cloud platform
  • Monitoring, logging and maintenance runbooks

Practical projects

01

Build a market overview dashboard with interactive price, return and volatility views over a local dataset

02

Develop a portfolio monitoring app with holdings upload, risk metrics and exportable reports

03

Deploy a multi-page analytics application with authentication, a FastAPI backend and containerized services

Skills you will practice

  • Plotly
  • Dash
  • Streamlit
  • FastAPI
  • PostgreSQL
  • Docker

Requirements

Who it's for

  • Python developers who want to ship financial tools to end users
  • Analysts who want to share research through interactive apps
  • Engineers preparing for full-stack fintech and SaaS courses

Prerequisites

  • Python Programming for Financial Markets or equivalent Python and pandas experience
  • Financial APIs & Data Engineering is helpful for the data layer

Learning format

  • Self-paced lessons with incremental build labs
  • Weekly feature assignments with code review
  • UI critique sessions during cohort runs
  • Capstone application with a recorded demo

Quantzivo certificates are completion credentials issued by Quantzivo, not accredited qualifications. Courses teach technical and research skills; they do not promise investment returns or provide investment advice.

Frequently asked questions

Self-paced lessons with incremental build labs Weekly feature assignments with code review UI critique sessions during cohort runs

Python Programming for Financial Markets or equivalent Python and pandas experience. See the full list under Requirements.

Yes. Completing the lessons and assessed projects earns a Quantzivo certificate of completion. It is a completion credential issued by Quantzivo, not an accredited qualification.

The $899 USD fee is a proposed launch price. Final fees, schedules, refund terms and any regional options are confirmed before any payment is taken.

Quantzivo teaches technical, data and research skills. It does not provide investment advice, trading signals or any promise of returns. Trading involves risk, including loss of capital.
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