AI Analyst with Power BI

Perform modern financial analysis using Microsoft Excel, Power BI, Microsoft Fabric, Artificial Intelligence (AI), and Copilot technologies.

0 Available Batches
3 Months Total
Advanced
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Program Overview

The Certified AI Financial Analyst with Power BI 2026 program is designed to equip learners with the knowledge, technical competencies, and practical skills required to perform modern financial analysis. The course aims to develop learners' ability to acquire, transform, model, analyze, visualize, and interpret financial data from multiple business sources, enabling them to generate actionable insights that support organizational decision-making.

Modules
12
Projects
1
Batches
0
Language
English
Acquire, transform, model, and manage financial data from multiple sources using Microsoft Excel, Power BI, Power Query, and Microsoft Fabric.
Develop and optimize financial analytics solutions using data modeling techniques, DAX calculations, KPIs, and business intelligence best practices.
Analyze and interpret financial performance, trends, variances, anomalies, and forecasts to support data-driven business decision-making.
Design and implement interactive dashboards, executive reports, and AI-enhanced decision-support solutions utilizing Power BI, Microsoft Fabric, and Copilot.

Available Course Batches

Live Registration Management

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Course Outline

12 Lessons
Expand All
01

Module 1: AI Financial Analyst with Power BI

5 core competencies

Establish a professional analytics workstation for financial data analysis
Import financial datasets into spreadsheet environments and analyze data structures
Clean and standardize financial datasets using data validation rules
Develop financial KPI worksheets to monitor organizational performance
Utilize AI-powered tools and prompt engineering for generating financial insights
02

Module 2: Excel for Financial Analytics

5 core competencies

Manage Excel workbooks and develop formulas for financial calculations
Apply logical, conditional, and lookup functions (e.g., XLOOKUP, IF statements)
Summarize financial datasets using Pivot Tables and aggregate transactional data
Design dashboard components and create charts to present financial information
Integrate analytical outputs into comprehensive financial management reports
03

Module 3: Power BI Fundamentals

5 core competencies

Navigate the Power BI Desktop interface and configure project workspaces
Connect Excel and CSV data sources to Power BI for analytical processing
Connect relational database sources (e.g., SQL Server) to Power BI
Profile imported datasets to assess data quality and completeness
Consolidate data from multiple business sources into a unified analytical model
04

Module 4: Data Transformation and Financial Data Preparation using Power Query

5 core competencies

Navigate Power Query Editor to manage data transformation workflows and cleansing
Standardize financial data formats, columns, and convert data types
Integrate related datasets using merge and join operations
Consolidate financial datasets from multiple reporting periods using append operations
Design end-to-end financial data preparation (ETL) workflows
05

Module 5: Financial Data Modeling

5 core competencies

Analyze business datasets to identify fact and dimension tables
Design relationships and evaluate cardinality between business entities
Design star schema models to support business intelligence solutions
Configure hierarchical structures for multidimensional drill-down analysis
Develop and validate integrated enterprise financial data models
06

Module 6: DAX Fundamentals for Financial Analytics

5 core competencies

Develop DAX calculated columns to enrich financial datasets
Develop DAX measures to aggregate business data and calculate financial metrics
Develop conditional calculations and KPI indicators using logical decision-making frameworks
Develop time-based analytical measures (MTD, QTD, YTD) for trend analysis
Integrate calculated columns and measures into executive scorecards
07

Module 7: Advanced Financial Analytics using DAX

5 core competencies

Develop advanced financial calculations using CALCULATE and filter context manipulation
Compare departmental performance using ranking and benchmarking methodologies (RANKX)
Develop cumulative analytical measures and time-series analytical models
Evaluate organizational performance through variance analysis (actuals vs. budgets)
Design comprehensive KPI frameworks supporting organizational performance management
08

Module 8: Financial Dashboard Design and Visualization

5 core competencies

Design dashboard layouts and wireframes aligned with executive reporting requirements
Develop charts and analytical visuals to communicate financial performance
Configure filters, slicers, and drill-through functionality for interactive reporting
Apply data storytelling techniques to communicate financial insights effectively
Develop and integrate enterprise-grade executive dashboards
09

Module 9: AI Financial Analytics

5 core competencies

Utilize AI-powered tools to generate and evaluate financial insights from datasets
Construct and refine effective prompts to support financial analysis and reporting
Analyze business datasets using AI to identify trends, anomalies, and potential risks
Generate financial forecasts and predictive planning scenarios using AI techniques
Integrate AI-generated insights and forecasting models into executive dashboards
10

Module 10: Microsoft Fabric for Financial Analytics

5 core competencies

Navigate and configure Microsoft Fabric workspaces for financial analytics projects
Develop Lakehouse solutions for centralized financial data storage and management
Develop enterprise data warehouses optimized for high-performance financial reporting
Develop dataflows and pipelines (Data Factory) to automate financial data preparation
Implement governance requirements, security controls, and access management policies
11

Module 11: AI-Powered Financial Analytics using Copilot and Fabric AI

5 core competencies

Utilize Microsoft Copilot to generate analytical insights using natural language
Refine prompt strategies and develop reusable prompt libraries for Copilot workflows
Analyze datasets using AI-assisted exploratory techniques to detect performance patterns
Generate financial forecasts and predictive scenarios using Fabric AI capabilities
Design unified AI-enabled financial intelligence solutions integrating Fabric, Power BI, and Copilot
12

Module 12: Capstone Project - AI Financial Intelligence Platform

5 core competencies

Define project scope, gather stakeholder requirements, and formulate objectives
Design and implement enterprise data models integrating multiple financial datasets
Develop executive dashboards (Revenue, Cost, Budget, and Forecasting Analytics)
Integrate AI-driven insights, forecasting models, and Copilot analytics into the platform
Present the final enterprise intelligence solution and defend analytical methodologies

Assigned Expert Faculty

No instructors assigned yet to this course.

Starting Seat Fee

Free
Batch StartsComing Soon
Duration3 Months

Core Target Tools

Microsoft Excel
Power BI Desktop
Power Query
DAX
Microsoft Fabric
Microsoft Copilot

Hiring Outlook

AI Financial Analyst
Business Intelligence Analyst
Data Analyst
Financial Planning & Analysis (FP&A) Professional

Strategic Career Roadmap

Mastering AI Analyst with Power BI for the Global Tech Market.

Through a structured progression from data preparation and financial modeling to advanced analytics and executive reporting, learners will gain hands-on experience in developing enterprise-grade business intelligence solutions aligned with industry best practices.

Industry Demand In Pakistan

The program further aims to develop learners' capabilities in applying AI-assisted analytics, predictive forecasting, anomaly detection, prompt engineering, and AI-driven decision-support techniques within financial environments.

Power BI Course LahoreFinancial Data Analytics TrainingMicrosoft Fabric AnalyticsLearn DAX for FinanceAI Financial Analyst Certification

Upon successful completion, learners will be able to design and implement integrated financial intelligence solutions, evaluate business performance through advanced analytical methodologies, and communicate data-driven recommendations to stakeholders.

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Frequently Asked Questions

Everything you need to know about AI Analyst with Power BI at AISD

What are the entry requirements for the AI Analyst with Power BI course?

The minimum requirement is Intermediate (FA/FSC/ICS/I.Com) or equivalent, with a preferred background in Commerce or Business. Basic computer literacy is required.

Which software tools will I learn to use?

The curriculum focuses on Microsoft Excel, Power BI Desktop, Power Query, DAX (Data Analysis Expressions), Microsoft Fabric, and AI productivity tools like Microsoft Copilot.

Will I learn how to clean and prepare data?

Yes. A significant portion of the course involves using Power Query to Extract, Transform, and Load (ETL) data, resolving quality issues, and integrating multiple data sources into a clean, analysis-ready format.

Does the course cover advanced Power BI concepts like DAX?

Absolutely. You will learn DAX fundamentals as well as advanced techniques, including calculating complex measures, utilizing time intelligence functions (YTD, MTD), and creating conditional KPIs.

Is there a practical project at the end of the course?

Yes. The final module is a Capstone Project where you will design, build, and present a comprehensive AI Financial Intelligence Platform that solves real-world business challenges.

Still have more questions?Contact AISD Support →