IBM
Generative AI: Elevate Your Data Science Career
IBM

Generative AI: Elevate Your Data Science Career

This course is part of multiple programs.

Rav Ahuja
Abhishek Gagneja
Dr. Pooja

Instructors: Rav Ahuja

Sponsored by University of Texas at Austin

12,101 already enrolled

Gain insight into a topic and learn the fundamentals.
4.7

(101 reviews)

Intermediate level

Recommended experience

12 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.7

(101 reviews)

Intermediate level

Recommended experience

12 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Leverage generative AI tools, like GPT 3.5, ChatCSV, and tomat.ai, available to Data Scientists for querying and preparing data

  • Examine real-world scenarios where generative AI can enhance data science workflows

  • Practice generative AI skills in hand-on labs and projects by generating and augmenting datasets for specific use cases

  • Apply generative AI techniques in the development and refinement of machine learning models

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

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When you enroll in this course, you'll also be asked to select a specific program.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 3 modules in this course

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.

What's included

9 videos2 readings3 assignments2 app items1 discussion prompt7 plugins

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.

What's included

6 videos1 reading3 assignments4 app items4 plugins

Enhance your data science with generative AI and complete the guided project and evaluation.

What's included

1 video3 readings1 assignment1 app item1 plugin

Instructors

Instructor ratings
4.7 (21 ratings)
Rav Ahuja
IBM
52 Courses3,029,025 learners

Offered by

IBM

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4.7

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