Intro to Gen AI Learning Path
This learning path provides a thorough overview of generative AI. This specialization delves into the ethical considerations that are essential for the responsible development and deployment of AI, as well as the foundations of large language models (LLMs) and their diverse applications.
Description for Intro to Gen AI Learning Path
Features of the Course:
- Provides a thorough overview of generative AI.
- Covers ethical considerations for responsible AI development and deployment.
- Explores foundations and diverse applications of large language models (LLMs).
- Includes interactive assessments throughout the modules.
- Assessments evaluate understanding of critical concepts and terminology.
- Immediate feedback is provided to reinforce learning and highlight areas for further investigation.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 11
Offered by: On Coursera offered by Google Cloud
Duration: 1 month at 10 hours a week
Schedule: Flexible
Pricing for Intro to Gen AI Learning Path
Use Cases for Intro to Gen AI Learning Path
FAQs for Intro to Gen AI Learning Path
Reviews for Intro to Gen AI Learning Path
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Intro to Gen AI Learning Path
Explore the use of generative AI tools to enhance data preparation, querying, and machine learning model development in data science workflows through hands-on projects.
Enhance your software development career with Gen AI. Develop hands-on, in-demand Generative AI skills to elevate your software engineering game in one month or less.
Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.
Develop generative AI capabilities for data analytics. Learn about generative AI to advance your career as a data analyst! No prior experience is required.
Comprehend generative AI basics, practical applications, ethical implications, and potential impacts on student learning in education.
Enhance your Product Manager career with Gen AI. Boost your Product Manager career in under two months by developing hands-on, in-demand generative AI skills. No prior experience is required to initiate the process.
Begin your vocation in generative AI data engineering. Obtain the necessary skills to secure a position as a data engineer by acquiring an understanding of generative AI. No prior experience is required.
Explore the evolution and business implications of generative AI, emphasizing data significance, governance, transparency, and practical applications in modernization and customer service in this course.
Acquire the knowledge necessary to direct your AI voyage. In this program, a CEO will instruct you on how to become a hands-on, AI-powered leader who is prepared to unlock the transformative potential of GenAI for your organization.
Featured Tools
Gain a foundational understanding of generative AI, including its functions, key concepts like large language models, datasets, and prompts, and the components used to build and operate AI solutions.
Master the art of machine learning in the field of marketing. This five-course Specialization from Jindal Global Business School (JGBS) is designed for marketing professionals and individuals who are interested in acquiring a more comprehensive understanding of the process of conceptualizing effective marketing strategies and decisions using Machine Learning (ML) and Decision Science.
Generative AI for Data Privacy & Protection' course delves into the intersection of Generative AI and data privacy strategies, targeting professionals to gain insights, investigate methodologies, and comprehend AI's impact on data privacy, with accessibility for diverse audiences regardless of prior knowledge.
Develop and evaluate machine learning models using regression, trees, and unsupervised techniques to address various business challenges.
Apply linear algebra concepts like linear independence, rank, singularity, eigenvalues, and eigenvectors to analyze data and solve machine learning problems using standard vector and matrix operations.