Generative AI for Data Science
Master the application of GenAI in data science. Learn data augmentation, feature engineering, and ethical AI implementation.
Master the application of GenAI in data science. Learn data augmentation, feature engineering, and ethical AI implementation.
This comprehensive course teaches data scientists how to leverage Generative AI in their projects. Students learn to implement GenAI applications including data augmentation, feature engineering, and anomaly detection. The curriculum covers running local LLMs, practical implementations in marketing and advertising, and crucial aspects of data security and privacy. Perfect for professionals looking to integrate cutting-edge AI technology into their data science workflow.
Instructors:
English
English (Original), العربية (آلي), Deutsch (Auto), 6 more
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What you'll learn
Master GenAI applications in data science and marketing
Implement data augmentation and feature engineering techniques
Run and deploy large language models locally
Analyze data security and privacy implications
Apply ethical considerations in GenAI implementations
Develop practical skills in anomaly detection
Skills you'll gain
This course includes:
64 Minutes PreRecorded video
5 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 5 modules in this course
This comprehensive course explores the integration of Generative AI in data science applications. The curriculum covers essential aspects from basic GenAI concepts to advanced implementations in data augmentation and feature engineering. Students learn practical skills in running large language models locally, implementing specific use cases, and addressing data security and privacy concerns. The course emphasizes both technical proficiency and ethical considerations in applying GenAI to data science challenges.
Generative AI for Data Science
Module 1 · 12 Minutes to complete
Lesson 1: Versatility and Impact of GenAI in Data Science
Module 2 · 22 Minutes to complete
Lesson 2: Running and deploying an LLM locally for Data Science
Module 3 · 33 Minutes to complete
Lesson 3: Feature Engineering with High Performance SMS Campaign Data
Module 4 · 60 Minutes to complete
Lesson 4: Ethical Considerations of GenAI
Module 5 · 60 Minutes to complete
Fee Structure
Payment options
Financial Aid
Instructor
Empowering Individuals and Organizations Through Technology
Microsoft's mission is "to empower every person and every organization on the planet to achieve more," reflecting its commitment to leveraging technology for global empowerment. The company aims to drive digital transformation through an integrated cloud approach, creating a robust platform that enhances productivity and accessibility for users worldwide. Its vision statement emphasizes the goal of democratizing artificial intelligence, ensuring that AI technologies are accessible and beneficial for everyone. This focus on empowerment and inclusivity underpins Microsoft's strategies and product development, positioning it as a leader in innovation within the technology sector. The company has consistently pursued excellence by fostering a culture of innovation, diversity, and corporate social responsibility, ultimately aiming to improve quality of life and facilitate progress across various fields, including education, healthcare, and business.
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Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.