Description for Data Engineering, Big Data, and ML on GCP Specialization
Features of Course
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
Learn to build machine learning solutions using Generative AI on AWS, including an understanding of AWS cloud computing and utilizing services like Amazon Bedrock.
Acquire the skills necessary to program powerful systems in Rust. Through projects in data engineering, Linux tools, DevOps, LLMs, Cloud Computing, and machine learning operations, acquire the skills necessary to develop software that is both efficient and robust, utilizing Rust's distinctive safety and speed.
Become an adept in the field of machine learning. Break into the field of artificial intelligence by mastering the fundamentals of deep learning. Recently upgraded with state-of-the-art methodologies!
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.
Become a machine learning engineer. Enhance your programming abilities with MLOps
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.
Acquire practical full stack development skills, knowledge of Cloud Native tools, proficiency in front-end development languages, and build a GitHub portfolio through hands-on tasks and a capstone project.
Featured Tools
Learn about various generative AI models and architectures, the application of LLMs in language processing, and implement NLP preprocessing techniques using libraries and PyTorch.
Gain expertise in Large Language Models (LLMs), apply generative AI to diverse tasks, ensure ethical alignment, and access the course regardless of prior AI or programming knowledge.
Develop and evaluate a neural network that can identify handwritten numerals, implement One Hot Encoding for classification, and evaluate the efficacy of the model through practical exercises.
Construct and train neural networks and tree ensemble methods using TensorFlow, while applying effective machine learning practices for real-world data generalization.
Begin to explore NLP. Learn the latest NLP techniques through four practical courses! Last updated in October 2021 to incorporate the most recent methodologies.
Compare & Review AI Tool Directory Best AI Course Marketplace
Aimed Labs