The_Role_of_Data_Science_in_Generative_AI.pptx

Abpt on role of data science in daily life

1. The Role of Data Science in Generative AI NAME: S.ESHWAR VIVEK ROLLNO:23N81A66J7

2. Introduction to Generative AI Generates new content: text, images, music, etc. Examples: ChatGPT, DALL·E, Midjourney , github copilot Built using ML & deep learning models

3. What is Data Science? Data Science is the field that focuses on extracting meaningful insights and knowledge from raw data using scientific methods, algorithms, and systems - Key steps: Data Collection Cleaning Analysis Visualization Tools: Python, R, SQL, Pandas

4. How Data Science Powers Generative AI Data is the foundation of learning Clean, labeled data improves performance AI models learn patterns from large datasets E.g., ChatGPT trained on billions of text files

5. Data Pipeline in Generative AI Data Collection: APIs, web scraping Data Cleaning: Remove Duplicates and errors Model Training & Evaluation : This is the process of teaching the AI model using historical data. Generation & Feedback : Once trained the model can now generate new content based on input prompts.

6. Real-world Examples Text: ChatGPT, Grammarly Images: DALL·E, Midjourney Code: GitHub Copilot Music: AI music from training data

7. Conclusion Data Science is the backbone of Generative AI Clean, diverse data = better AI A powerful combination for future automation & creativity