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Rav Ahuja, Abhishek Gagneja, and Dr. Pooja

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.

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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.

Enroll now

What's inside

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.
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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.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a strong foundation for beginners interested in the field
Suitable for those currently working as or aspiring to work as data scientists
Teaches in-demand and industry-relevant skills
Emphasizes real-world applications
Addresses important ethical considerations
Includes practical exercises and projects

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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 Generative AI: Elevate Your Data Science Career with these activities:
Review Statistics
Refresh your foundational understanding of statistics and data analysis to prepare for the data science concepts introduced in the course.
Browse courses on Statistics
Show steps
  • Review core statistical concepts such as measures of central tendency, probability, and hypothesis testing.
  • Practice solving statistical problems to reinforce your understanding.
Review Data Science for Business by Foster Provost & Tom Fawcett
Review this book to strengthen your foundations in data science, specifically as it pertains to business applications.
Show steps
  • Read and digest key chapters
  • Take notes on important concepts
  • Complete end-of-chapter exercises
Follow the official Generative AI tutorials
These tutorials will help you get started with generative AI and learn how to use it in your own projects.
Browse courses on Generative AI
Show steps
  • Find the official tutorials
  • Follow the instructions
  • Complete the exercises
Five other activities
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Show all eight activities
Help other students in the Coursera discussion forums
By helping others, you'll reinforce your own understanding of the material and build your communication skills.
Show steps
  • Identify a question that you can answer
  • Write a thoughtful and helpful response
  • Post your response in the forum
Solve LeetCode problems tagged as 'easy'
Solving these problems will help you improve your problem-solving skills in data science, which is essential for success in the field.
Browse courses on Problem Solving
Show steps
  • Pick a problem
  • Understand the problem statement
  • Design an algorithm
  • Implement the algorithm
  • Test your solution
Attend a generative AI workshop
This will help you to get a deeper understanding of the latest generative AI techniques and how to apply them in practical settings.
Browse courses on Generative AI
Show steps
  • Find a workshop that interests you
  • Register for the workshop
  • Attend the workshop
  • Complete the exercises
Build a simple data visualization tool
This will strengthen your understanding of how to use generative AI to speed up data visualizations.
Browse courses on Data Visualization
Show steps
  • Identify a dataset
  • Choose the right visualization type
  • Build the visualization
  • Test and refine the visualization
Contribute to popular GitHub repositories
By contributing to GitHub repositories, you'll learn how to build and contribute to open source projects and stay updated on the latest industry trends.
Browse courses on Open Source
Show steps
  • Find a project to contribute to
  • Set up your development environment
  • Make a small contribution
  • Submit a pull request
  • Review feedback and make changes

Career center

Learners who complete Generative AI: Elevate Your Data Science Career will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists play a major role in today's digital business world. Business leaders rely on their expertise to analyze vast amounts of data, extract meaningful insights, and make data-driven decisions to boost revenue, increase efficiency, and reduce risk. Generative AI is becoming mainstream, and data scientists can boost their careers by taking courses like this that feature leading-edge, in-demand, generative AI skills.
Machine Learning Engineer
Machine Learning Engineers design, implement, and manage machine learning systems for real-world applications. Generative AI is an emerging field within machine learning, and learning about it can help Machine Learning Engineers to build more effective and efficient systems.
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns that can help businesses make better decisions. Generative AI can help Data Analysts to improve the quality and accuracy of their data.
Software Engineer
Software Engineers design, develop, and maintain software applications. They may also work on the underlying infrastructure that supports these applications, including cloud computing platforms. Generative AI may not be a core part of the role, but knowledge of it can give Software Engineers an edge in the industry.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze and forecast financial data. Generative AI can help Quantitative Analysts to develop more accurate and sophisticated models.
Business Analyst
Business Analysts help businesses understand their data and make better decisions. Generative AI can help Business Analysts to identify trends and patterns that would be difficult to find manually.
Data Engineer
Data Engineers design, build, and maintain the infrastructure that supports data science and machine learning applications. Generative AI can help Data Engineers to create more efficient and scalable data pipelines.
Product Manager
Product Managers are responsible for the development and launch of new products. Generative AI can help Product Managers to understand their customers' needs and develop products that meet those needs.
Data Science Manager
Data Science Managers lead teams of data scientists and machine learning engineers. They are responsible for setting the strategic direction for their teams and ensuring that they are meeting the business's needs. Generative AI can help Data Science Managers to make better decisions about how to allocate their resources and to identify new opportunities for growth.
Market Researcher
Market Researchers study market trends and consumer behavior to help businesses make informed decisions about their products and services. Generative AI can help Market Researchers to collect and analyze data more efficiently and to develop more accurate forecasts.
Statistician
Statisticians collect, analyze, and interpret data to help businesses make better decisions. Generative AI can help Statisticians to develop more accurate and sophisticated models.
Financial Analyst
Financial Analysts use financial data to help businesses make informed decisions about their investments. Generative AI can help Financial Analysts to develop more accurate and sophisticated models.
Risk Manager
Risk Managers identify and assess risks that could affect a business's operations. Generative AI can help Risk Managers to develop more accurate and sophisticated models.
Auditor
Auditors examine financial records to ensure that they are accurate and complete. Generative AI can help Auditors to identify fraud and other financial irregularities.
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. Generative AI can help Actuaries to develop more accurate and sophisticated models.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Generative AI: Elevate Your Data Science Career.
This beginner-friendly guide to GANs complements the course's introduction to advanced generative AI models. It provides a solid foundation for further exploration.
This classic provides a comprehensive overview of data science, including data generation, preparation, and analysis. It supplements the course's focus on generative AI.
This comprehensive textbook introduces deep learning, providing a theoretical foundation for generative AI models. It serves as a valuable reference for advanced learners.
This practical guide to NLP with Python supplements the course's coverage of text generation and analysis. It provides hands-on experience with real-world NLP tasks.
This classic textbook provides a comprehensive overview of pattern recognition and machine learning. It offers a deeper understanding of the theoretical foundations of generative AI.
This thought-provoking book explores the challenges of aligning AI with human values. It raises important ethical questions related to the use of generative AI.

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