Google Cloud Digital Leader Training Professional Certificate
Acquire a basic understanding of digital transformation and cloud computing. Boost your cloud confidence to enable you to engage in discussions with colleagues in technical cloud positions and make informed business decisions regarding cloud technology.
Description for Google Cloud Digital Leader Training Professional Certificate
Features of Course
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud Training
Duration: 1 month at 10 hours a week
Schedule: Flexible
Pricing for Google Cloud Digital Leader Training Professional Certificate
Use Cases for Google Cloud Digital Leader Training Professional Certificate
FAQs for Google Cloud Digital Leader Training Professional Certificate
Reviews for Google Cloud Digital Leader Training Professional Certificate
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Google Cloud Digital Leader Training Professional Certificate
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.
Learn how to use Gemini for Google Workspace to boost productivity and efficiency in Gmail through its generative AI features.
Learn to leverage Google Cloud's data-to-AI tools, generative AI capabilities, and Vertex AI for comprehensive ML model development.
Learn to use Vertex AI on Google Cloud for no-code AutoML model development, training, and deployment, while integrating ML with cloud tools and adhering to Responsible AI principles.
Outlines methods to determine main products, develop streaming pipelines, explore alternatives, and define essential steps for machine learning workflows on Google Cloud.
Data Engineering on Google Cloud. Embark on a vocation in data engineering. Provide business value through the application of machine learning and big data.
Explore the functionality, practical applications, limitations, and advancements of diffusion models, including their text-to-image applications.
This course explores enterprise machine learning applications, assesses the viability of ML use cases, and addresses the prerequisites, data characteristics, and critical factors for developing and managing ML models.
The course introduces Google Cloud fundamentals for transforming business models with data, ML, and AI, targeting those interested in cloud AI/ML impacts on business without requiring prior experience, and excludes hands-on technical training.
Featured Tools
This program provides a pragmatic introduction to machine learning and data mining using R, encompassing fundamental techniques and tackling significant data analysis difficulties.
Gain practical skills to implement models in Python across diverse industries while exploring machine learning and deep learning concepts.
Mastering Advanced Statistics for Data Science. Acquire the necessary knowledge and abilities to effectively communicate the choices and interpretations of models.
Master Generative AI to improve productivity, automate tasks, and enhance creativity in real-world applications. Develop practical skills, from foundational knowledge to advanced prompt engineering.
Confidently navigate the realm of data. Acquire the necessary skills in AI, scientific reasoning, and data analysis to facilitate informed decision-making.