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Soheil Haddadi and Reza Moradinezhad

"GenAI for Data Scientist" is designed for professionals eager to integrate Generative AI (GenAI) into their data science practices. This introductory course breaks down the complex world of GenAI, demonstrating its significant impact on data analysis, predictive modeling, and beyond. You will learn the technical workings of GenAI tools and their practical applications in real-world data science scenarios.

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"GenAI for Data Scientist" is designed for professionals eager to integrate Generative AI (GenAI) into their data science practices. This introductory course breaks down the complex world of GenAI, demonstrating its significant impact on data analysis, predictive modeling, and beyond. You will learn the technical workings of GenAI tools and their practical applications in real-world data science scenarios.

This course is designed for team leads and managers looking to incorporate GenAI into their strategic initiatives, as well as individual data scientists and analysts eager to enhance their daily tasks with advanced GenAI techniques. It is also suitable for professionals aiming to advance their careers by mastering cutting-edge GenAI applications in data science.

Learners should have a basic understanding of data analytics, statistical methods, and machine learning, along with familiarity with programming languages like Python or R. An open mindset and eagerness to explore new technologies are also essential.

The curriculum covers the fundamentals of machine learning models, data augmentation, and ethical considerations, providing insights into how GenAI can enhance analytical precision and foster innovation.

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What's inside

Syllabus

GenAI for Data Scientist
The course aims to build a strong foundational understanding of GenAI, enabling data scientists to explore innovative ways to apply these technologies in their daily tasks. By the end of the course, learners will have a clear grasp of the capabilities and limitations of GenAI, setting the stage for more advanced studies or immediate application in their professional roles.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides an entry point for professionals to apply GenAI in their data science toolkit, regardless of their industry background
Suitable for beginners in the field of Generative AI, providing a strong foundation for further exploration
Taught by experts Soheil Haddadi and Reza Moradinezhad, known for their contributions to the field of Generative AI
Examines the applications of Generative AI across various domains of data science, showcasing its versatility
Requires foundational knowledge of data analytics, statistical methods, and machine learning, which may limit accessibility for complete beginners

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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 Scientists with these activities:
Review statistical methods
Reinforce your existing understanding of statistical methods, ensuring a solid foundation for GenAI techniques.
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  • Revise core statistical concepts such as probability, distributions, and hypothesis testing.
  • Practice applying statistical methods to real-world data analysis scenarios.
Attend Industry Meetups and Conferences on GenAI
Connect with professionals in the field to gain insights and learn about latest trends in GenAI.
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  • Research industry meetups and conferences focused on GenAI.
  • Register and attend events that align with your interests.
  • Engage in discussions, ask questions, and exchange ideas with attendees.
  • Follow up with potential mentors or collaborators.
Practice using GenAI tools
Develop proficiency in utilizing GenAI tools, enhancing your hands-on experience and solidifying your understanding.
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  • Experiment with various GenAI tools to generate data, images, or text.
  • Apply GenAI tools to solve real-world data science problems.
Three other activities
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Practice GenAI Techniques on a Sample Data Science Project
Reinforce your understanding of GenAI by applying techniques to a practical data science scenario.
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  • Choose a sample data science project from a platform like Kaggle or GitHub.
  • Identify data augmentation and predictive modeling techniques to enhance your project.
  • Implement GenAI tools and algorithms within your project.
  • Evaluate the impact of GenAI on the accuracy and insights derived from your project.
Develop a GenAI-Powered Data Analysis Dashboard
Demonstrate your understanding of GenAI by creating a powerful data analysis dashboard that incorporates GenAI techniques.
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  • Identify a suitable dataset and research relevant GenAI techniques
  • Design and implement the dashboard using a GenAI-powered platform
  • Evaluate the performance and impact of the dashboard
Build a GenAI-powered data analysis project
Apply your GenAI and data science skills by creating a project that showcases your proficiency and deepens your understanding.
Show steps
  • Identify a real-world data science problem that can be addressed using GenAI.
  • Design and develop a GenAI solution to solve the problem.
  • Evaluate the performance of your GenAI solution and draw meaningful conclusions.
  • Present your project and findings to an audience.

Career center

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

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