Description for ML on Google Cloud
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 2 months at 10 hours a week (approximately)
Schedule: Flexible
Pricing for ML on Google Cloud
Use Cases for ML on Google Cloud
FAQs for ML on Google Cloud
Reviews for ML on Google Cloud
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML on Google Cloud
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.
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.
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Utilize Generative AI to optimize marketing creativity. Explore the potential of Generative AI to revolutionize and influence your marketing organization.
Learn the significance, use cases, history, and pros and cons of generative AI in a business context, with a focus on its relationship to machine learning and services at Amazon.
Acquire practical skills to build a generative AI application by constructing a retrieval augmented generation (RAG) system using data, Qdrant, and LLMs.
Learn to build machine learning solutions using Generative AI on AWS, including an understanding of AWS cloud computing and utilizing services like Amazon Bedrock.
The "Introduction to Vertex AI" course provides a four-hour, practical, and fundamental overview of Vertex AI, ideal for professionals and enthusiasts aiming to leverage AI effectively.
Investigate the field of artificial intelligence and machine learning. While investigating the transformative disciplines of artificial intelligence, machine learning, and deep learning, enhance your Python abilities.
Featured Tools
The course encompasses the following topics: the development of a text processing pipeline, the comprehension of Naive Bayes classifier theory, and the assessment of the efficacy of classification models following training.
Gain proficiency in the development of machine learning models and big data pipelines by utilizing Google Cloud's state-of-the-art tools, such as BigQuery, Dataflow, Vertex AI, and Pub/Sub.
Optimize and interpret machine learning functions using gradients, derivatives, and gradient descent in neural networks.
This project guides you in setting up and using an Azure Computer Vision Cognitive Services resource to make API calls, providing foundational skills for AI and Machine Learning solutions in Microsoft Azure.
Become proficient in the programming and analysis of data using Python. Create software that collects, cleans, analyzes, and presents data.