Sales Forecasting and Trend Prediction with AI
Participant will understand how AI can drive accurate forecasts and strategic planning to optimize revenue and inventory management.
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Training TypeLive Training
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CategoryArtificial Intelligence
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Duration4 Hours
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Rating4.9/5
Course Introduction
About the Course
This course covers how Artificial Intelligence (AI) can be used to improve sales forecasting and predict market trends. Participants will learn the foundational AI models and techniques for analyzing sales data, predicting demand, and identifying future trends.
Course Objective
Through real-world applications, they’ll understand how AI can drive accurate forecasts and strategic planning to optimize revenue and inventory management.
Who is the Target Audience?
Sales and marketing managers
Business analysts and financial planners
Product managers focused on demand planning and forecasting
Business leaders interested in leveraging AI for data-driven decision-making
Basic Knowledge
Basic understanding of sales and marketing operations
Familiarity with data analysis concepts is helpful but not required
Related Virtual Classroom
Available Batches
| 28 Jan 2025 | Tue ( 1 Day ) | 12:00 PM - 04:00 PM (Eastern Time) |
| 28 Feb 2025 | Fri ( 1 Day ) | 12:00 PM - 04:00 PM (Eastern Time) |
| 31 Mar 2025 | Mon ( 1 Day ) | 12:00 PM - 04:00 PM (Eastern Time) |
Pricing
Live
Single Attendee
149
249
Live Session
Recorded
Single Attendee
199
332
6 month Access for Rec
Live+Recorded
Single Attendee
249
416
6 month Access for Rec
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Curriculum
Total Duration : 4 Hours
Introduction to AI in Sales Forecasting
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Overview of AI and Its Role in Forecasting
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Key Concepts: Machine Learning, Time Series Analysis, and Predictive Analytics
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Business Value of AI-Driven Sales Forecasting
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Case Studies: AI Applications in Sales Forecasting
Core AI Techniques for Forecasting and Trend Prediction
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Machine Learning Models for Sales Prediction (Linear Regression, Decision Trees, etc.)
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Time Series Models: ARIMA, Exponential Smoothing, and LSTM (Long Short-Term Memory)
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Feature Engineering for Sales Data
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Using AI for Seasonal and Cyclical Trend Analysis
Building and Interpreting AI Forecasting Models
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Setting Up Forecasting Models with Real-World Sales Data
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Training and Testing AI Models for Accuracy
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Understanding AI Model Outputs: Predictions and Confidence Intervals
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Interactive Exercise: Model Interpretation and Adjustment
Practical Applications of AI in Sales Forecasting
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Inventory Management: Aligning Supply with Demand Forecasts
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Pricing Strategies and Dynamic Pricing Models
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Market Trend Analysis: Predicting Emerging Trends
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Case Study: Optimizing Revenue with AI Forecasting
Ethical and Operational Considerations
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Data Privacy and Compliance in Sales Forecasting
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Mitigating Bias in Predictive Models
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Operationalizing AI in Forecasting Processes
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Building Trust and Transparency with AI Predictions
Future Trends in AI for Forecasting
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Emerging AI Techniques: Reinforcement Learning, AutoML
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The Role of Big Data and Real-Time Forecasting
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Future Skills and Tools for AI in Sales Forecasting
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Q&A and Interactive Discussion