Google AI Essentials
Generative AI facilitates daily tasks, decision-making, and idea generation, emphasizing responsible use, leveraging prompting techniques, and staying updated on AI advancements.
Description for Google AI Essentials
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 2
Offered by: On Coursera provided by Google
Duration: 3 weeks at 3 hours a week
Schedule: Flexible
Pricing for Google AI Essentials
Use Cases for Google AI Essentials
FAQs for Google AI Essentials
Reviews for Google AI Essentials
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Google AI Essentials
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.
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.
Featured Tools
With an emphasis on fairness measurement methods, the course teaches students how to use the Aequitas Tool to identify bias in machine learning models.
This AI course instructs data scientists on the development of automated algorithms using Watson Studio's AutoAI, with an emphasis on hyperparameter optimization, feature engineering, and model selection.
Acquire the ability to differentiate between static and dynamic training and inference, manage model dependencies, establish distributed training for defect tolerance and replication, and generate exportable models.
Learn to use TensorFlow for computer vision and natural language processing, manage image data, prevent overfitting, and train RNNs, GRUs, and LSTMs on text repositories.
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.