GenAI for Data Scientists
Learn to integrate Generative AI into data science workflows. Master synthetic data generation, model building, and ethical AI implementation.
Learn to integrate Generative AI into data science workflows. Master synthetic data generation, model building, and ethical AI implementation.
This comprehensive course introduces data scientists to the transformative potential of Generative AI in data analysis and modeling. Designed for both team leads and individual practitioners, it covers practical applications of GenAI tools for synthetic data generation, predictive modeling, and code generation. The curriculum emphasizes hands-on experience with tools like Gemini and ChatGPT while addressing ethical considerations.
Instructors:
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What you'll learn
Recognize GenAI capabilities and limitations in data science
Master synthetic data generation techniques
Implement predictive modeling with GenAI tools
Perform text classification using OpenAI API
Conduct exploratory data analysis with ChatGPT
Develop responsible AI integration strategies
Skills you'll gain
This course includes:
94 Minutes PreRecorded video
1 assignment,1 peer review
Access on Mobile, Tablet, Desktop
FullTime access
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There is 1 module in this course
This course provides a comprehensive introduction to integrating Generative AI into data science practices. Students learn practical applications including synthetic data generation, machine learning model creation, and code conversion across programming languages. The curriculum covers using tools like Gemini for predictive modeling, ChatGPT for exploratory data analysis, and OpenAI API for text classification. Special emphasis is placed on ethical considerations and responsible AI integration.
GenAI for Data Scientists
Module 1 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructors
Data Scientist and AI Research Scientist
Soheil Haddadi is a postdoctoral researcher specializing in Artificial Intelligence (AI) and machine learning, with a robust academic background in Control and Automation Systems Engineering. His expertise encompasses a wide range of areas, including data science, deep learning, natural language processing (NLP), and robotics. Soheil is committed to advancing the field of AI through innovative research and practical applications.He teaches several courses on Coursera, such as Fine-tuning Language Models for Business Tasks, GenAI for Data Scientists, and Data Engineering: Pipelines, ETL, Hadoop. These courses are designed to equip learners with the skills necessary to effectively utilize generative AI technologies and data engineering practices in various professional contexts.
AI Educator and Human-Centered Interaction Researcher
Reza Moradinezhad is an AI educator and researcher dedicated to promoting trustworthy AI and enhancing human-centered interactions. He holds a PhD in Computer Science from Drexel University and currently serves as an assistant teaching professor at Drexel's College of Computing & Informatics. In addition, he is an AI Scientist at TulipAI, where he focuses on ethical and responsible use of generative AI technologies.Reza offers a variety of courses on Coursera, including Building Production-Ready Apps with Large Language Models, Evaluating Large Language Model Outputs: A Practical Guide, and GenAI for Application Developers. His courses aim to equip learners with the skills necessary to effectively utilize large language models in various applications, from customer service to data analysis.
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