Introduction to AI and ML on GC - Espanol
Learn how to develop AI and ML on Google Cloud with tools that are specifically designed to facilitate seamless integration throughout the data-to-AI lifecycle.
Description for Introduction to AI and ML on GC - Espanol
Features of the Course:
Comprehensive Data-to-AI Tools: Comprehend the technologies and tools offered by Google Cloud to facilitate the development, implementation, and maintenance of AI foundations.
Generative AI Projects: Develop generative AI applications by utilizing Gemini's multimodal instructions and model refining.
AI Project Development: Acquire a comprehensive understanding of the diverse methods available for the development of AI projects that are customized to meet the specific needs of users on Google Cloud.
End-to-End Machine Learning: Utilize Vertex AI to construct and deploy comprehensive ML models and pipelines for practical applications.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 3 weeks at 3 hours a week
Schedule: Flexible
Pricing for Introduction to AI and ML on GC - Espanol
Use Cases for Introduction to AI and ML on GC - Espanol
FAQs for Introduction to AI and ML on GC - Espanol
Reviews for Introduction to AI and ML on GC - Espanol
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Introduction to AI and ML on GC - Espanol
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.
The AI tool tailors advertisements using deep learning, facilitates multi-platform analysis, provides a custom view interface, streamlines creative testing, and offers insightful performance data, trusted by enterprises for its reliability and effectiveness.
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.
This course will provide you with an understanding of the technical underpinnings and essential terminology associated with generative artificial intelligence (AI).
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.
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.
Featured Tools
Learn to use the latest LLM APIs, the LangChain Expression Language (LCEL), and develop a conversational agent.
Learn to construct and implement prediction functions, understand overfitting and error rates, and grasp machine learning techniques like classification trees and regression.
The course highlights the curriculum focused on statistics and machine learning, covering descriptive statistics, data clustering, predictive model development, and analysis capability development.
Construct and train neural networks and tree ensemble methods using TensorFlow, while applying effective machine learning practices for real-world data generalization.
Explore the constraints, ethical dilemmas, responsible use, and economic and social implications of generative AI.