Building and Operating ML Solutions with Azure
The subject matter addresses the Azure ML Python SDK for the development and administration of enterprise machine learning applications, as a component of the DP-100 certification program.
Description for Building and Operating ML Solutions with Azure
Comprehensive Utilization of Azure ML SDK: Master the Azure Machine Learning Python SDK for the development and administration of scalable machine learning solutions.
Data and Computational Management: Comprehend the utilization of data and computational resources in Azure Machine Learning for enhanced model training efficiency.
Model Training and Data Safeguarding: Utilize the Azure ML SDK to train models, identify the appropriate model, and enforce data protection protocols for sensitive information.
Deployment of Real-Time Machine Learning Services: Design and implement pipelines for the deployment of real-time machine learning services with Azure Machine Learning.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 21
Offered by: On Coursera provided by Microsoft
Duration: 3 weeks at 10 hours a week
Schedule: Flexible
Pricing for Building and Operating ML Solutions with Azure
Use Cases for Building and Operating ML Solutions with Azure
FAQs for Building and Operating ML Solutions with Azure
Reviews for Building and Operating ML Solutions with Azure
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Building and Operating ML Solutions with Azure
Examine how to improve learning and preserve integrity by incorporating morally sound and useful AI tools into evaluation procedures.
Acquire practical expertise in the integration of machine learning models into pipelines, optimizing performance, and efficiently managing versioning and artifacts.
Learn how to use AI technologies for personal development and active learning, embrace continuous learning, and cultivate a growth mindset.
Understand foundational knowledge of AI and RegTech, their societal implications, and the discourse around their future integration and obstacles.
This training provides professionals with knowledge and practical advice on AI ethics, compliance issues, and risk management.
Gain extensive knowledge in AI technologies relevant to digital marketing, involving precise data analysis, content creation, and tools for optimizing social media and consumer segmentation.
Study the ethical consequences of AI development and implementation, emphasizing generative AI, AI governance, and pragmatic ethical decision-making in practical contexts.
Gain proficiency in the automation of software development processes through the utilization of generative artificial intelligence, AI-assisted programming, MLOps, and Amazon Web Services.
Learn the skills necessary to operate, optimize, and implement large language models through practical experience with state-of-the-art LLM architectures and open-source resources.
Develop expertise in the exposure and deployment of large language models via application programming interfaces (APIs), configure server environments, and incorporate natural language processing (NLP) functionalities into applications.
Featured Tools
An extensive study of the applications of AI in marketing, ranging from competitive analysis to content optimization and conversion enhancement.
This course covers Python programming, TensorFlow for linear regression, and app development for stock market prediction.
Discover AI terminology, ethical norms, and protocols for responsibly utilizing and citing Generative AI.
This program instructs instructors on the ethical and successful integration of AI, while promoting innovation and critical thinking among students.
A thorough grasp of artificial intelligence (AI) and machine learning, including its various forms, methods, and applications, is given in this course.
Compare & Review AI Tool Directory AI Course Marketplace
