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Generative AI

Elevate Your Data Science Career

Rav Ahuja, Abhishek Gagneja, and Dr. Pooja

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.

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.

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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.

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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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Traffic lights

Read about what's good

what should give you pause

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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Reviews summary

Practical generative ai for data science

According to learners, this course offers a practical and highly relevant introduction to Generative AI for data science. Many found the content on data augmentation, feature engineering, and model building particularly insightful. Students appreciate the hands-on projects and labs, which help solidify understanding and provide tangible skills. While most consider it a valuable tool for career advancement, some note that it assumes prior data science knowledge, suggesting it's best for those looking to elevate existing skills rather than starting from scratch. The inclusion of ethical considerations is frequently highlighted as a significant positive.

Comprehensive and unique coverage of AI ethics.

"The ethical considerations module was also a valuable addition, often overlooked in other courses."

"The emphasis on ethics was commendable, providing crucial insights."

"The ethical considerations section was a standout, I found it very insightful."

Strong emphasis on practical, hands-on components.

"The hands-on coding and projects are the strongest part of the course for me."

"The labs were helpful, though I wished for more diverse examples."

"The real-world applications and hands-on components were outstanding."

Focuses on real-world data science problems.

"The hands-on project was incredibly useful for solidifying concepts like data augmentation and feature engineering."

"The focus on real-world data science problems using Generative AI was a major plus."

"I learned how to use practical tools and strategies that I could apply immediately to my work."

Pacing can be inconsistent; some topics superficial.

"Disappointed with the depth... high-level overview rather than providing the 'elevate' experience."

"Felt a bit superficial for an 'elevate your career' course."

"The course is okay, but I felt it moved too quickly through some core AI concepts."

"The course is decent, but some modules felt rushed and inconsistent in their depth."

Requires prior data science or AI knowledge.

"If you're not already familiar with machine learning or neural networks, you might struggle."

"It's more of an 'elevate' course, not a 'learn from scratch' one."

"I'd say it's best for those with a foundational understanding of data science..."

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

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Refresh your foundational understanding of statistics and data analysis to prepare for the data science concepts introduced in the course.

Browse courses on Statistics

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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

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Review this book to strengthen your foundations in data science, specifically as it pertains to business applications.

View Data Science for Business: What You Need to... on Amazon

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Read and digest key chapters
Take notes on important concepts
Complete end-of-chapter exercises

Follow the official Generative AI tutorials

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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

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Find the official tutorials
Follow the instructions
Complete the exercises

Five other activities

Expand to see all activities and additional details

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Help other students in the Coursera discussion forums

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By helping others, you'll reinforce your own understanding of the material and build your communication skills.

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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'

Show steps

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

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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

Show steps

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

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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

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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.

See salaries and explore the career path for Data Scientist

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.

See salaries and explore the career path for Machine Learning Engineer

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.

See salaries and explore the career path for Data Analyst

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.

See salaries and explore the career path for Software Engineer

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.

See salaries and explore the career path for Quantitative Analyst

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.

See salaries and explore the career path for Business Analyst

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.

See salaries and explore the career path for Data Engineer

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.

See salaries and explore the career path for Product Manager

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.

See salaries and explore the career path for Data Science Manager

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.

See salaries and explore the career path for Market Researcher

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.

See salaries and explore the career path for Statistician

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.

See salaries and explore the career path for Financial Analyst

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.

See salaries and explore the career path for Risk Manager

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.

See salaries and explore the career path for Auditor

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. Generative AI can help Actuaries to develop more accurate and sophisticated models.

See salaries and explore the career path for Actuary

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.

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Cover image

Grokking Machine Learning

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This beginner-friendly guide to GANs complements the course's introduction to advanced generative AI models. It provides a solid foundation for further exploration.

Grokking Machine Learning

Grokking Machine Learning

Cover image

Cover image

Data Science for Business

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This classic provides a comprehensive overview of data science, including data generation, preparation, and analysis. It supplements the course's focus on generative AI.

Data Science for Business: What You Need to Know...

Data Science for Business: What You Need to Know...

Cover image

Cover image

Save

This comprehensive textbook introduces deep learning, providing a theoretical foundation for generative AI models. It serves as a valuable reference for advanced learners.

Deep Learning (Adaptive Computation and Machine...

Deep Learning (Adaptive Computation and Machine...

Cover image

Cover image

Natural Language Processing with Python

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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.

Natural Language Processing with Python: Analyzing...

Natural Language Processing with Python: Analyzing...

Pattern Recognition and Machine Learning

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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.

Pattern Recognition and Machine Learning...

Pattern Recognition and Machine Learning...

Pattern Recognition and Machine Learning (text...

Unknown Binding

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Cover image

The Alignment Problem

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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.

The Alignment Problem

The Alignment Problem

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Course image

Effort

3 weeks of study, 2-3 hours/week

Level

Intermediate

Via

Coursera

Institution

IBM

Instructors

Rav Ahuja

Abhishek Gagneja

Dr. Pooja

Language

English

Transcripts

Español Français Português Deutsch Italiano 中文 العربية 한국어 日本語 हिंदी Nederlands Svenska Pусский Türkçe Polski Ελληνικά українська мова magyar nyelv Bahasa Indonesia ไทย

This course belongs to a collection called Generative AI for Data Scientists. It's comprised of one courses:

Generative AI: Elevate Your Data Science Career (viewing)

Traffic lights

Read about what's good

what should give you pause

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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