Practical Evolution of Data Science with GenAI

Overview

Explore how GenAI is transforming data science workflows through case studies, comparisons with traditional AI, and insights into future trends and challenges in this practical conference talk.

Syllabus

• Introduction to GenAI in Data Science
Definition and Key Concepts
Overview of GenAI Applications
• Comparative Analysis: GenAI vs. Traditional AI
Core Differences
Strengths and Limitations
• Case Studies in GenAI Transformations
Automation of Data Preprocessing
Advanced Predictive Modeling
Innovative Data Visualization Techniques
• Practical Application and Workflow Integration
Tools and Platforms
Best Practices for Incorporation
• Future Trends and Innovation in GenAI for Data Science
Emerging Technologies and Techniques
Potential Industry Impacts
• Addressing Challenges and Ethical Considerations
Data Privacy and Security
Bias and Fairness in GenAI Models
• Conclusion and Q&A Session
Recap of Key Insights
Open Discussion on Future Directions

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Subjects

Data Science