AWS Certified Machine Learning - Specialty
AWS Certified Machine Learning Practice Tests - Complete Explanations and References that covers all MLS-C01 topics!
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What You Will Learn!
- What to expect on the AWS Certified Machine Learning Specialty exam
- Amazon SageMaker's built-in machine learning algorithms (XGBoost, BlazingText, Object Detection, etc.)
- Feature engineering techniques, including imputation, outliers, binning, and normalization
- High-level ML services: Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more
- Data engineering with S3, Glue, Kinesis, and DynamoDB
- Exploratory data analysis with scikit_learn, Athena, Apache Spark, and EMR
- Deep learning and hyperparameter tuning of deep neural networks
- Automatic model tuning and operations with SageMaker
- L1 and L2 regularization
- Applying security best practices to machine learning pipelines
Description
AWS Certified Machine Learning - Specialty
Become an AWS Certified Machine Learning - Specialty with this comprehensive course!
The AWS Certified Machine Learning - Specialty is an advanced certification that validates your ability to design, build, deploy, and manage machine learning models on AWS. With this certification, you can demonstrate your expertise in using AWS services such as Amazon SageMaker, Amazon Rekognition, and Amazon Comprehend to solve complex business problems.
In this course, you will learn the advanced concepts and skills required to pass the AWS Certified Machine Learning - Specialty exam. You will cover machine learning algorithms, data preprocessing, model training, and model deployment. You will also receive hands-on practice with real-world machine learning scenarios.
By the end of this course, you will be able to:
Design and build machine learning models on AWS.
Preprocess and prepare data for machine learning.
Train and evaluate machine learning models.
Deploy and manage machine learning models in production.
Who should take this course:
This course is for experienced data scientists and machine learning engineers who want to advance their skills and knowledge of AWS machine learning. This includes data scientists and machine learning engineers who work with AWS on a daily basis, data scientists and machine learning engineers who want to prepare for the AWS Certified Machine Learning - Specialty exam, and data scientists and machine learning engineers who want to learn more about advanced AWS machine learning concepts.
What you will need to take this course:
A computer with internet access
A basic understanding of machine learning principles
Experience with AWS services such as Amazon SageMaker, Amazon Rekognition, and Amazon Comprehend
Here are some of the benefits of taking this course:
Learn from experienced instructors: Our instructors are all AWS Certified Machine Learning - Specialty experts with years of experience in the field.
Get hands-on practice: You will receive hands-on practice with real-world machine learning scenarios.
Prepare for the AWS Certified Machine Learning - Specialty exam: You will receive comprehensive practice questions and mock exams to help you prepare for the AWS Certified Machine Learning - Specialty exam.
Get lifetime access: Once you purchase the course, you will have lifetime access to the materials and resources.
Enroll in this course today and take your first step towards becoming an AWS Certified Machine Learning - Specialty!
The AWS Certified Machine Learning Specialty certification is for developers and data scientists who want to validate their machine learning skills on the AWS platform. Specifically, the exam tests a candidate’s ability to design, build, deploy and maintain machine learning solutions. This path covers the four key test domains: Data Engineering, Exploratory Data Analysis, Modeling, and Machine Learning Implementation and Operations. The information and resources contained in this path will be vital in preparing to take the AWS Certified Machine Learning Specialty exam.
Just like the real exam, this practice exam tests four different domains:
Data Engineering
Exploratory Data Analysis
Modeling
Machine Learning Implementation and Operations
You'll need deep and broad knowledge of SageMaker and AWS's other machine learning services, including Rekognition, Translate, Polly, and Comprehend. You'll need to know how to process big data using Kinesis, S3, Glue, and Athena. And you'll need a strong knowledge of AWS security, including use of KMS and IAM.
But AWS knowledge is not enough to pass this practice exam, or the real thing! You also need deep knowledge on data science, feature engineering and tuning your machine learning models. Do you really understand regularization techniques and how to use them? Do you really understand precision, recall, and AUC? Do you know how different deep learning models work, and how they are used? This practice exam will let you find out. Every question includes an explanation of the correct answer as well.
Who Should Attend!
- Individuals performing a development or data science role seeking certification in machine learning and AWS.
- Machine learning professionals testing their readiness for the AWS Certified Machine Learning Specialty exam.
- IT Professionals who are planning to take the AWS Certified Machine Learning Specialty exam
- Students and professionals who want to deepen their knowledge in AWS