Description for ML in the Enterprise
Data Administration, Oversight, and Preprocessing: Acquire the skills to articulate and implement data management, governance methodologies, and preprocessing strategies within a machine learning workflow.
Vertex AutoML, BigQuery ML, and Custom Training: Comprehend the appropriate contexts for employing Vertex AutoML, BigQuery ML, and custom training to enhance model creation and deployment.
Vertex Vizier Hyperparameter Optimization: Utilize Vertex Vizier for hyperparameter optimization to improve model performance and precision.
Batch and Online Predictions, Model Surveillance, and Pipelines: Acquire expertise in generating batch and online predictions, establishing model monitoring, and constructing pipelines utilizing Vertex AI.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 19 hours (approximately)
Schedule: Flexible
Pricing for ML in the Enterprise
Use Cases for ML in the Enterprise
FAQs for ML in the Enterprise
Reviews for ML in the Enterprise
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML in the Enterprise
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.
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world
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
This course�trains on source code summary and programming language identification with Vertex AI LLM within Google Cloud.
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.
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.
The course outlines the learning objectives for understanding XGBoost algorithm theory, performing exploratory data analysis, and implementing XGBoost classifier models using Scikit-Learn.
Gain foundational knowledge of Linear Algebra and Machine Learning models, explore the scalability of SparkML and Scikit-Learn, and gain practical experience by adjusting models and analyzing vibration sensor data in a real-world IoT example.