AI in Financial Analysis and Forecasting

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Mentor Based

Program Syllabus

Module 1

About This Course

This self-paced program covers the role of AI in financial analysis and forecasting, focusing on financial data analytics, predictive modeling, and real-world applications. Participants will study case studies and prepare for key AI certifications in finance.

Module 2

Aim

To equip PhD scholars and academicians with advanced skills in leveraging AI for financial analysis and predictive forecasting. This course aims to enhance financial data analytics, predictive modeling, and real-world applications using AI-driven tools.

Module 3

Program Objectives

Implement AI-driven financial data analytics tools.
Develop and apply predictive models for financial forecasting.
Analyze successful case studies of AI in finance.
Prepare for AI certifications in financial analysis.
Enhance financial decision-making with AI insights.

Module 4

Program Structure

Financial Data Analytics
- Tools like Alteryx for financial data analysis
- Benefits and challenges of AI in financial analytics
- Hands-on session with AI data analytics tools
Predictive Modeling
- AI models for financial forecasting
- Implementing predictive analytics in finance
- Practical applications and case studies
Case Studies
- Real-world applications of AI in finance
- Analysis of successful implementations
- Lessons learned and best practices
Certification Insights
- Important topics for finance AI certifications
- Study materials and resources
- Practice exams and review sessions

Lead Instructor

Dr. Sarah Chen

PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.

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