Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
Start your Machine Learning career. Prepare for AWS Certified Machine Learning Specialty Certification by learning AWS ML basics.
Description for Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Whizlabs
Duration: 1 month at 10 hours a week
Schedule: Flexible
Pricing for Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
Use Cases for Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
FAQs for Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
Reviews for Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
Begin your vocation in generative AI data engineering. Obtain the necessary skills to secure a position as a data engineer by acquiring an understanding of generative AI. No prior experience is required.
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.
Investigate the objectives and advantages of Google's Big Data and Machine Learning products, including the use of BigQuery for interactive analysis, Cloud SQL, and Dataproc for migrating MySQL and Hadoop applications, and the selection of a variety of data processing tools on Google Cloud.
This AI course instructs data scientists on the development of automated algorithms using Watson Studio's AutoAI, with an emphasis on hyperparameter optimization, feature engineering, and model selection.
With practical experience in platform architecture and data querying, this course offers a basic understanding of data engineering, covering important ideas, tools, and career pathways.
With case studies on image analysis and natural language processing, this course focuses on applying various models, analyzing metrics, and setting up models and data pipelines.
In summary, this course covers Python, SQL, and database administration, which are fundamentals for a career in data engineering.
Featured Tools
This specific course emphasizes the integration of machine learning and AI with big data administration, utilizing Google Cloud services.
This course outlines the steps to create, preprocess, and evaluate an image classifier using Python code and sample images.
Gain a foundational understanding of generative AI, including its functions, key concepts like large language models, datasets, and prompts, and the components used to build and operate AI solutions.
Achieve a professional status as an AI Engineer. Acquire the knowledge necessary to develop next-generation applications that are propelled by generative AI, a skill that is indispensable for startups, agencies, and large corporations.
Explore LLM potential, address limitations, devise business strategies, and stay updated on LLM trends for effective implementation in business operations.