Module 320 minutes
Predictive Analytics for Beginners
Make predictions using AI—no data science degree required. Forecast trends and make data-driven decisions.
predictive-analyticsforecastingtrendspredictions
Learning Objectives
- ✓Understand basic predictive analytics concepts
- ✓Forecast trends using AI assistance
- ✓Identify patterns in historical data
- ✓Make predictions without coding
Predict the Future (Sort Of)
AI makes predictive analytics accessible to non-data scientists. Make better forecasts and decisions.
Simple Forecasting with AI
Trend projection prompt:
My sales data for last 12 months:
[Jan: $X, Feb: $Y, ... Dec: $Z]
Using simple trend analysis:
- What's the pattern?
- Forecast next 3 months
- Confidence level?
- Key assumptions?
Identifying Patterns
Pattern recognition:
Data: [paste your time series data]
Analyze for:
- Seasonal patterns
- Growth trends
- Anomalies
- Cyclical behaviors
What patterns exist and what do they mean?
Google Sheets Forecasting
FORECAST function:
I have:
- Historical data: A2:A13 (12 months)
- Time periods: B2:B13
Create FORECAST formula to predict next 3 months.
Walk me through setup.
Scenario Planning
AI scenario analysis:
Current metrics: [list]
Create 3 scenarios:
1. Optimistic (20% growth)
2. Realistic (10% growth)
3. Pessimistic (flat)
For each: expected outcomes and key drivers
Key Takeaways
- →AI can identify patterns in your historical data and project trends forward
- →Simple forecasting beats guessing—even basic predictions improve decisions
- →Always understand assumptions behind predictions—AI will explain them
- →Use scenario planning: optimistic, realistic, pessimistic outcomes
- →Predictions are probabilities, not certainties—plan accordingly
Practice Exercises
Apply what you've learned with these practical exercises:
- 1.Forecast your key metric for next quarter using AI
- 2.Identify seasonal patterns in your annual data
- 3.Create 3-scenario forecast for a business decision
- 4.Compare AI prediction to what actually happened (learn from variance)