What Does MVP Stand For? It’s Not What You Think.
October 7, 2024
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Recommended experience
Intermediate level
Learners should have a fundamental understanding of data science principles and strategies and an eagerness to learn and adapt to new technologies.
Recommended experience
Intermediate level
Learners should have a fundamental understanding of data science principles and strategies and an eagerness to learn and adapt to new technologies.
A comprehensive understanding of how GenAI technologies can be applied in a data science team, enhancing data quality and model development.
GenAI tools to automate and optimize data augmentation, to automate repetitive tasks such as data manipulation, model development, etc.
The ethical implications and best practices for integrating GenAI within data science team projects to ensure responsible and effective use.
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"GenAI for Data Science Teams" is an introductory course designed to bridge the gap between generative AI (GenAI) technologies and data science practices. This course aims to demystify GenAI complexities, enabling data science professionals to leverage these technologies for data augmentation, task automation, and model development.
This course is designed for data science managers and team leads aiming to foster innovation, senior data scientists driving GenAI adoption, aspiring data scientists looking to enter the field with advanced skills, and IT professionals seeking to understand GenAI's applications in data science for cross-disciplinary innovation. Learners should have a fundamental understanding of data science principles and strategies, along with an eagerness to learn and adapt to new technologies. By the end of this course, learners will be able to creatively apply GenAI tools in their workflows, enhancing project outcomes and driving team innovation.
"GenAI for Data Science Teams" is an introductory course designed to bridge the gap between generative AI (GenAI) technologies and data science practices. This course aims to demystify the complexities surrounding GenAI, making it accessible for data science professionals to leverage these technologies for enhancing data augmentation, automating repetitive tasks, and model development. Through engaging content and practical applications, learners will gain a solid foundation in understanding how GenAI can revolutionize data handling, analysis, and model training processes.
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