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IBM

Generative AI: Elevate Your Data Science Career

IBM via Coursera

Overview

Generative AI is now mainstream. Boost your career with a course that features leading-edge, in-demand, generative AI skills tuned to the needs of data scientists. This course is suitable for existing and aspiring data scientists, data professionals, analysts, and engineers. The course addresses real-world data science problems data scientists encounter—across multiple industries— with data generation, data augmentation, and feature engineering. Gain skills you can immediately put to use implementing generative AI models and techniques that address these real-world issues. Then, learn how to use generative AI to speed data visualizations, build models and to produce data insights. You’ll also learn about key ethics considerations around generative AI and data, key concerns for executives across industries. Demonstrate your new generative AI skills in a hands-on data augmentation and feature engineering project that you can apply in your real-life profession. Then complete your final quiz to earn your certificate. You can share both your project and certificate with your current or prospective employers.

Syllabus

  • Data Science and Generative AI
    • In this module, you will explore the role of generative AI in data science. Lesson 1 introduces you to generative AI and how it can serve various purposes in the hands of data scientists. You will learn about the four common types of generative AI models and their impact and applications across diverse industries. Lesson 2 will cover how data scientists can leverage generative AI in the data science lifecycle. You will learn how data scientists can effectively use generative AI to perform data generation, data preparation, data querying, and data augmentation. You will also learn about data preparation and querying challenges and how generative AI models can help tackle these challenges.
  • Use of Generative AI for Data Science
    • In this module, you will explore the role of generative AI in data science. Lesson 1 will cover generative AI for understanding data and model building. You will learn how data scientists can use generative AI to visualize, develop, and build models. Lesson 2 will cover the use of generative AI for data science regarding tools and techniques to help in exploratory data analysis (EDA) and develop a predictive model. You will learn about the industry-specific considerations while using generative AI and the challenges data scientists face. You will also learn about the skills data scientists require to succeed in their field and how generative AI can help them hone those skills in today’s world.
  • Final Project and Exam
    • Enhance your data science with generative AI and complete the guided project and evaluation.

Taught by

Rav Ahuja, Abhishek Gagneja and Dr. Pooja

Reviews

4.7 rating at Coursera based on 73 ratings

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