- Prompt Engineering
- Marketing
- Data Ethics
- Generative AI
- Feature Engineering
- Anomaly Detection
- Operational Efficiency
- Advertising
- Large Language Modeling
- Artificial Intelligence
- Application Deployment
- Data Synthesis
Generative AI for Data Science
Completed by Sayan Chowdhury
March 18, 2025
3 hours (approximately)
Sayan Chowdhury's account is verified. Coursera certifies their successful completion of Generative AI for Data Science
What you will learn
Proficiency in Gen AI within the data science landscape, specifically in marketing and advertising.
Exposure to many Gen AI applications, including data augmentation, feature engineering, anomaly detection, and generative modeling.
Run large language models locally, identify and implement specific use cases for GenAI, and join conversations about data security and privacy.
Explore ethical and operational implications of Gen AI in data science, and integrate its innovative potential into practices through integrity.
Skills you will gain
