Description for Innovating with Google Cloud Artificial Intelligence
Key Concepts in AI and Machine Learning: Investigate the fundamental principles and methodologies of AI and ML.
Business Value of Machine Learning: Discover how machine learning can generate value and stimulate expansion in business applications.
Google Cloud AI and ML Services: Analyze the selection of artificial intelligence and machine learning products that Google Cloud provides.
Practical Business Applications: Comprehend the process of aligning AI and ML tools with organizational objectives to optimize their impact.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 1 hour (approximately)
Schedule: Flexible
Pricing for Innovating with Google Cloud Artificial Intelligence
Use Cases for Innovating with Google Cloud Artificial Intelligence
FAQs for Innovating with Google Cloud Artificial Intelligence
Reviews for Innovating with Google Cloud Artificial Intelligence
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Innovating with Google Cloud Artificial Intelligence
The AI tool empowers non-programmers to construct and deploy AI, featuring data transformation, insights generation, identification of critical drivers, and prediction and forecasting functionalities to enhance business decision-making and planning processes.
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.
Achieve a professional status as an AI Engineer. Acquire the knowledge necessary to develop next-generation applications that are propelled by generative AI, a skill that is indispensable for startups, agencies, and large corporations.
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.
Delve into the historical evolution of Generative AI and AI, exploring diverse models and their applications in business contexts for optimized decision-making and innovation.
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.
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.
Begin your professional journey as an AI Product Manager. Develop generative AI and product management skills that are in high demand to be job-ready in six months or less.
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Featured Tools
The curriculum is designed to assist participants in achieving operational excellence and responsible innovation by assisting them in mastering AI governance under ISO/IEC 42001.
Master inventive thinking techniques and their application in routine problem-solving and addressing global challenges by selecting and implementing the appropriate approach for each situation.
Learn the principles, advantages, components, and deployment strategies of multi-cloud computing for enhanced resilience, scalability, and adaptability.
Begin to explore NLP. Learn the latest NLP techniques through four practical courses! Last updated in October 2021 to incorporate the most recent methodologies.
Learn to differentiate between deep learning, machine learning, and artificial intelligence (AI), select the appropriate AWS machine learning service for specific use cases, and understand the process of developing, training, and deploying machine learning models.