AI In Business Analysis Full Syllabus

Duration: 8–10 Weeks | Level: Beginner to Intermediate
Perfect For: Aspiring Business Analysts, Entrepreneurs, Data Professionals, MBAs, Product Managers
Goal: Learn how to use Artificial Intelligence to make smarter business decisions, analyze data, predict trends, and automate tasks.

Module 1: Introduction to AI in Business Analysis

• What is AI in simple business terms?
• Traditional Business Analysis vs. AI-driven Analysis
• Why AI is a game-changer for business decision-making
• Real-world success stories from top companies (Amazon, Netflix, etc.)

Task: List 3 business processes in your field that can be improved by AI

Module 2: Understanding the Business Analyst’s Evolving Role

• Core responsibilities of a Business Analyst
• New skills needed in the AI era
• AI + Human = Augmented Intelligence
• Where analysts fit in modern data pipelines

Activity: Match common business problems to AI-powered solutions

Module 3: Basics of AI, Machine Learning & Data Science (Non-Technical)

• Simple explanation of AI, ML, Deep Learning
• Types of machine learning (with business examples)
• Predictive vs Prescriptive analytics
• How businesses “train” AI using data

Mini Quiz: Classify examples into AI/ML/Traditional Analytics

Module 4: Data Collection, Cleaning & Exploration

• What kind of data businesses need (internal vs external)
• Basics of data preparation (cleaning, organizing)
• Exploratory Data Analysis (EDA) concepts
• Tools used: Excel, Power BI, Python (optional), Google Sheets, Tableau

Hands-on: Clean and analyze sample sales data using Excel or Power BI

Module 5: Predictive Analytics for Smarter Decisions

• What is Predictive Modeling?
• Forecasting customer behavior, demand, revenue, churn
• Popular algorithms (simplified): Regression, Classification
• Use-cases: inventory forecasting, lead scoring, sales trends

Project: Predict sales for the next quarter based on previous data

Module 6: AI Tools Every Business Analyst Should Know

• Power BI with AI visuals
• Google Analytics + GA4 + predictive insights
• Excel AI features
• Tableau AI-driven dashboards
• ChatGPT / Copilot / Replit AI for documentation & reports
• No-code AI tools: MonkeyLearn, DataRobot, Akkio

Task: Create an AI-powered dashboard showing KPI trends

Module 7: Sentiment Analysis & Customer Insights

• What is sentiment analysis?
• How businesses understand customer feedback using AI
• Use-cases: Product reviews, customer support, social media analysis
• Tools: MonkeyLearn, Lexalytics, Hugging Face (optional)

Hands-on: Analyze real Amazon reviews or tweets to find customer pain points

Module 8: AI in Strategic Planning & Risk Management

• Using AI to identify business opportunities and threats
• Scenario modeling and simulations
• Fraud detection using anomaly detection
• Business continuity planning with predictive insights

Case Study: How an insurance company reduced fraud using AI

Module 9: Automation in Business Analysis

• What is RPA (Robotic Process Automation)?
• Using AI to automate reports, alerts, workflows
• Tools: Power Automate, Zapier, UiPath
• ChatGPT for generating summaries, meeting notes, etc.

Mini Project: Set up an automation to send weekly business report emails

Module 10: Ethics, Risks, and Future of AI in Business Analysis

• Bias in AI: When predictions go wrong
• Responsible AI: transparency and fairness
• Data privacy and security concerns
• The future: AI copilots, self-service analytics, decision intelligence

Discussion: Should business decisions rely fully on AI?

Final Capstone Projects (Choose One)

1. Build a business dashboard with AI-powered sales prediction
2. Analyze social media data to improve customer engagement
3. Create a business report where AI helped reduce costs
4. Use ChatGPT to automate reporting for a small business

Key Outcomes

After this course, you’ll be able to:

• Think like a modern Business Analyst in the AI era
• Use AI tools to interpret data and solve business problems
• Communicate insights clearly using dashboards and reports
• Automate basic tasks using no-code AI platforms
• Make ethical, data-driven business recommendations

Recommended Tools (Mix of Free + Paid)