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URL: https://www.coursera.org/learn/automate-financial-insights-with-ai-tools--dashboards

⇱ Automate Financial Insights with AI Tools & Dashboards | Coursera


Automate Financial Insights with AI Tools & Dashboards

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Automate Financial Insights with AI Tools & Dashboards

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Design interactive dashboards using Power BI, Tableau, and Streamlit that communicate clear and actionable financial insights.

  • Integrate machine learning models into dashboards and web apps for real-time forecasting and data-driven decision support.

  • Automate financial reporting workflows using data pipelines, scheduled refreshes, and alert systems.

  • Implement API-driven data ingestion workflows using financial data sources such as Yahoo Finance and FinancialModelingPrep.

Details to know

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Recently updated!

March 2026

Assessments

16 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Master Financial Analysis: AI-Driven Modeling & Forecasting Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

Learn how to automate financial insights end-to-end by building real-time data pipelines, AI-powered dashboards, and interactive financial applications. In this course, you will use APIs, ETL workflows, Power BI, Tableau, Streamlit, ML models, and LLM-based AI tools to deploy production-ready financial analytics systems.

In Module 1, you will explore automation foundations for finance by working with financial APIs, ETL pipelines, and workflow orchestration tools while implementing governance, auditability, and error handling. In Module 2, we will cover dashboard design and real-time financial visualization using Power BI and Tableau, including automated refresh, forecasting visuals, and alerting mechanisms. In Module 3, you will see how to build interactive financial applications using Streamlit, integrate ML models and real-time data, and deploy cloud-hosted analyst tools. In Module 4, we will bring everything together in a capstone project by building a fully automated, AI-enabled financial insights platform with APIs, ML forecasting, dashboards, LLM commentary, alerts, and monitoring. By the end, you will be able to: -Build automated financial data pipelines using APIs and ETL workflows -Create real-time dashboards with Power BI, Tableau, and Streamlit -Integrate ML models and LLM-generated insights into analytics systems -Deploy cloud-ready, end-to-end financial automation solutions This course is ideal for: -FP&A, finance, and investment professionals seeking automation skills -Analysts building dashboards and real-time reporting systems -Data professionals working on financial analytics platforms -Learners completing a finance + AI specialization or capstone Transform static financial reports into automated, AI-powered insight systems used by modern finance teams. Disclaimer: This is an independent educational resource created by Board Infinity for informational and educational purposes only. This course is not affiliated with, endorsed by, sponsored by, or officially associated with any company, organization, or certification body unless explicitly stated. The content provided is based on industry knowledge and best practices but does not constitute official training material for any specific employer or certification program. All company names, trademarks, service marks, and logos referenced are the property of their respective owners and are used solely for educational identification and comparison purposes.

Learn how automation is applied in modern finance roles by working with APIs, ETL pipelines, and workflow orchestration tools. Build reliable, auditable financial automation systems with proper governance and error handling.

What's included

10 videos5 readings4 assignments1 discussion prompt1 plugin

10 videosβ€’Total 90 minutes
  • Course Welcome Video!β€’2 minutes
  • What Automation Means in Modern Finance Rolesβ€’10 minutes
  • Automation Use Cases Across FP&A, Treasury & Investment Researchβ€’9 minutes
  • Data Sources for Automated Financial Workflowsβ€’10 minutes
  • How APIs Work and How Analysts Use Themβ€’8 minutes
  • Pulling Market and Macro Data from Financial APIsβ€’11 minutes
  • API Authentication, Rate Limits and Error Handlingβ€’9 minutes
  • ETL Concepts for Financial Data Pipelinesβ€’11 minutes
  • Scheduling Automated Workflows Using Airflowβ€’10 minutes
  • No-Code Automation Using n8n and Zapierβ€’9 minutes
5 readingsβ€’Total 65 minutes
  • Syllabusβ€’10 minutes
  • Glossaryβ€’10 minutes
  • Read more about Finance Automation, AI & Modern FP&A Practicesβ€’15 minutes
  • Read more about Using APIs to Access Market and Economic Dataβ€’15 minutes
  • Read more about ETL, ELT & Automated Data Pipelines in Financeβ€’15 minutes
4 assignmentsβ€’Total 150 minutes
  • Graded Quiz: Automation Foundations for Financial Analystsβ€’60 minutes
  • Practice Quiz : β€” Introduction to Modern Automation in Financeβ€’30 minutes
  • Practice Quiz : β€” APIs for Financial Dataβ€’30 minutes
  • Practice Quiz : β€” ETL & Workflow Orchestrationβ€’30 minutes
1 discussion promptβ€’Total 5 minutes
  • Can Automation Elevate Your Finance Career?β€’5 minutes
1 pluginβ€’Total 5 minutes
  • Quick Course Check-inβ€’5 minutes

Design and build KPI-driven dashboards for FP&A, investors, and risk teams. Connect dashboards to automated data pipelines and implement forecasting visuals and alert mechanisms.

What's included

9 videos3 readings4 assignments

9 videosβ€’Total 89 minutes
  • Types of Financial Dashboardsβ€’11 minutes
  • Designing KPI-Driven Financial Dashboardsβ€’10 minutes
  • Best Practices for Financial Storytellingβ€’9 minutes
  • Connecting Power BI to Financial Data Sourcesβ€’12 minutes
  • Building Financial Visuals for Performance and Forecastingβ€’10 minutes
  • Automated Refresh, Parameters and DAX Fundamentalsβ€’11 minutes
  • Connecting Tableau to Live and Extract Dataβ€’9 minutes
  • Advanced Financial Visualizations in Tableauβ€’8 minutes
  • Interactive Dashboard Actions and Storytellingβ€’9 minutes
3 readingsβ€’Total 45 minutes
  • Read more about Financial Dashboard Design & KPIsβ€’15 minutes
  • Read more about Power BI for Financial Reporting, Modeling & Time Intelligenceβ€’15 minutes
  • Read more about Tableau for Financial Dashboards, Visual Analytics & Storytellingβ€’15 minutes
4 assignmentsβ€’Total 150 minutes
  • Graded Quiz : β€” Dashboards for Real-Time Financial Insightsβ€’60 minutes
  • Practice Quiz : β€” Dashboard Fundamentals & Design Principlesβ€’30 minutes
  • Practice Quiz : β€” Power BI for Financial Visualizationβ€’30 minutes
  • Practice Quiz : β€” Tableau for Financial Storytellingβ€’30 minutes

Build interactive financial applications using Streamlit and integrate ML models with real-time data. Deploy secure, cloud-hosted tools that enable live forecasting and user interaction.

What's included

9 videos3 readings4 assignments1 discussion prompt

9 videosβ€’Total 92 minutes
  • Streamlit Basics: Layouts, Widgets and Data Loadingβ€’13 minutes
  • Creating Interactive Financial Componentsβ€’13 minutes
  • App Theming, Deployment and Sharingβ€’10 minutes
  • Loading Machine Learning Models into Streamlitβ€’10 minutes
  • Adding Forecast Inputs and Predictive Outputsβ€’11 minutes
  • Visualizing Machine Learning Outputsβ€’10 minutes
  • Connecting Applications to APIs and Live Dataβ€’8 minutes
  • Deploying Financial Applications to the Cloudβ€’8 minutes
  • Authentication, Permissions and Version Controlβ€’9 minutes
3 readingsβ€’Total 45 minutes
  • Read more about Building and Deploying Financial Dashboards with Streamlitβ€’15 minutes
  • Read more about Deploying Machine Learning Models in Streamlit for Financeβ€’15 minutes
  • Read More: Taking Streamlit Apps from Live Data to Secure Cloud Deploymentβ€’15 minutes
4 assignmentsβ€’Total 150 minutes
  • Graded Quiz : β€” Interactive Applications for Modern Analystsβ€’60 minutes
  • Practice Quiz : β€” Building Financial Applications with Streamlitβ€’30 minutes
  • Practice Quiz : β€” Integrating Machine Learning Models into Appsβ€’30 minutes
  • Practice Quiz : β€” Real-Time Data Integration & Cloud Deploymentβ€’30 minutes
1 discussion promptβ€’Total 5 minutes
  • Turn a Model into a Client-Ready Toolβ€’5 minutes

Apply everything you’ve learned to build a production-ready, AI-driven financial analytics platform. Integrate APIs, ETL, ML forecasting, dashboards, LLM commentary, and automated alerts.

What's included

10 videos3 readings4 assignments

10 videosβ€’Total 88 minutes
  • Connecting Real-Time APIs for Market and Macro Dataβ€’10 minutes
  • Machine Learning Forecasting Using Prophet and Gradient Boostingβ€’9 minutes
  • Automated Data Cleaning and Feature Generationβ€’10 minutes
  • Linking Dashboards to API and Machine Learning Outputsβ€’9 minutes
  • Setting Alerts for Thresholds, Volatility and Variancesβ€’9 minutes
  • Automated Insight Delivery via Notificationsβ€’9 minutes
  • Generative AI for Financial Commentaryβ€’9 minutes
  • Sentiment Analysis and Forecast Narrative Generationβ€’11 minutes
  • Responsible AI Usage and Risk Evaluationβ€’10 minutes
  • Course Closure!β€’2 minutes
3 readingsβ€’Total 40 minutes
  • Read More: Building Production-Grade Time Series Forecasting Systems with Pythonβ€’15 minutes
  • Read More: Building Automated Alerting & Monitoring Systems for Financial Dashboardsβ€’15 minutes
  • Case Study: Automating Financial Insights in Real-World Finance Teams β€’10 minutes
4 assignmentsβ€’Total 150 minutes
  • Graded Quiz : β€” Capstone: AI-Enabled Automated Financial Insights Systemβ€’60 minutes
  • Practice Quiz : β€” Building the Data & Forecasting Backboneβ€’30 minutes
  • Practice Quiz : β€” Automated Dashboards and Alertsβ€’30 minutes
  • Practice Quiz : β€” LLM Commentary & Insights Generationβ€’30 minutes

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Instructor

Board Infinity
261 Coursesβ€’428,186 learners

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Frequently asked questions

Yes. You’ll build pipelines, dashboards, apps, and a full capstone system.

Helpful but not required. Power BI, Tableau, and Streamlit are taught step by step.

APIs, Python, Airflow, n8n, Zapier, Power BI, Tableau, Streamlit, and LLM tools.

Yes. You’ll deploy Streamlit apps using cloud-ready platforms.

Yes. The final capstone is a complete automated financial insights system.

Yes. You’ll generate commentary, insights, and sentiment-based narratives.

Yes. Monitoring, versioning, auditability, and responsible AI are included.

Approximately 4 weeks with 4–5 hours per week.

Learners ready to operationalize financial analysis and ML into production systems.

Yes. These skills align with modern FP&A, analytics engineering, and AI roles.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,