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Soheil Haddadi and Reza Moradinezhad

"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.

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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.

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What's inside

Syllabus

GenAI for Data Science Teams
"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.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Designed for data science professionals seeking to leverage GenAI technologies for data augmentation, task automation, and model building
Ideal for individuals seeking to advance their data science skills and incorporate cutting-edge GenAI techniques into their workflows
Conducted by instructors Soheil Haddadi and Reza Moradinezhad, who bring expertise and experience in the field of Generative AI
Part of a comprehensive curriculum on GenAI for Data Science Teams, offering a structured learning path for learners seeking to master this technology
Provides a foundational understanding of GenAI and its applications in data science, catering to learners with a fundamental understanding of data science principles

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in GenAI for Data Science Teams with these activities:
Review basic data science principles
Refreshing your understanding of fundamental data science principles will help you better grasp the more advanced concepts covered in this course.
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  • Review textbooks or online resources on data science basics
  • Work through practice problems or tutorials on data manipulation and analysis
Complete tutorials on generative AI (GenAI) technologies
Hands-on practice with tutorials will provide a deeper understanding of how GenAI tools work and how to apply them in data science projects.
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  • Find tutorials on platforms like Coursera, edX, or YouTube
  • Follow the tutorials step-by-step
  • Experiment with different GenAI techniques
Discuss GenAI applications with peers
Engaging in discussions with peers will broaden your perspective on GenAI applications and challenges.
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  • Join online forums or discussion groups dedicated to GenAI
  • Participate in discussions and share your insights
Four other activities
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Compile a list of GenAI resources
Creating a collection of resources will help you stay updated on the latest developments in GenAI and provide a valuable reference for future projects.
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  • Search for GenAI-related articles, tutorials, and tools
  • Organize and categorize the resources
Practice using GenAI tools for data augmentation
Regular practice with data augmentation techniques will enhance your proficiency in using GenAI tools to generate realistic synthetic data.
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  • Set up a development environment for data augmentation
  • Experiment with different data augmentation techniques
  • Evaluate the effectiveness of augmented data on model performance
Develop a GenAI-based solution for a real-world problem
Applying your knowledge to a real-world project will solidify your understanding of GenAI techniques and their practical applications.
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  • Identify a suitable problem that can be addressed with GenAI
  • Design and develop a GenAI-based solution
  • Evaluate the performance of your solution
Initiate a side project exploring GenAI applications
Working on a personal project will allow you to apply your GenAI knowledge in a practical setting and foster creativity.
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  • Identify a project idea that interests you
  • Gather resources and experiment with GenAI techniques
  • Develop and deploy your project

Career center

Learners who complete GenAI for Data Science Teams will develop knowledge and skills that may be useful to these careers:

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