Description for Data Engineering, Big Data, and ML on GCP Specialization
Level: Intermediate
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 Data Engineering, Big Data, and ML on GCP Specialization
Use Cases for Data Engineering, Big Data, and ML on GCP Specialization
FAQs for Data Engineering, Big Data, and ML on GCP Specialization
Reviews for Data Engineering, Big Data, and ML on GCP Specialization
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Data Engineering, Big Data, and ML on GCP Specialization
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world
Gain the skills needed for a machine learning engineering role and prepare for the Google Cloud Professional Machine Learning Engineer certification exam by learning to design, build, and productize ML models using Google Cloud technologies.
Gain practical experience in optimizing, deploying, and scaling machine learning models using Google Cloud Platform through a structured five-course specialization with hands-on labs and a focus on advanced topics and recommendation systems.
Construct and train neural networks and tree ensemble methods using TensorFlow, while applying effective machine learning practices for real-world data generalization.
Learn to develop, train, and assess neural networks using TensorFlow to resolve classification issues by understanding the fundamental principles of neural networks.
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.
Master the process of exploratory data analysis, train AutoML models with Vertex AI and BigQuery ML, optimize models using performance metrics and loss functions, and generate scalable datasets for training and evaluation.
Learn to load data, create features, and build and evaluate both supervised and unsupervised models in BigQuery for fraud and anomaly detection.
Featured Tools
Generative AI for Your Benefit. Utilize Generative AI to develop and instruct personalized assistants.
Comprehend generative AI basics, practical applications, ethical implications, and potential impacts on student learning in education.
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.
Developing a Strategic Advantage through the Mastery of Generative AI. Leverage the transformative potential of Generative AI to empower your leadership suite.
Explore the evolution and business implications of generative AI, emphasizing data significance, governance, transparency, and practical applications in modernization and customer service in this course.
Compare & Review AI Tool Directory AI Course Marketplace
