AWS Certified Machine Learning Engineer Associate Prep

AWS Certified Machine Learning Engineer Associate Prep, available at $44.99, has an average rating of 5, with 24 lectures, based on 18 reviews, and has 313 subscribers.

You will learn about Introduction to AWS and Machine Learning Data Engineering Exploratory Data Analysis (EDA) Machine Learning on AWS Model Deployment and Monitoring Machine Learning Frameworks Deep Learning AWS Machine Learning Services Big Data and Machine Learning Security and Compliance This course is ideal for individuals who are This course is ideal for Data Scientists and Machine Learning Engineers looking to validate and enhance their AWS machine learning skills, IT professionals interested in specializing in machine learning and cloud computing, students and graduates aspiring to build a career in these fields, and professionals seeking certification to pass the AWS Certified Machine Learning Engineer – Associate exam. It is particularly useful for This course is ideal for Data Scientists and Machine Learning Engineers looking to validate and enhance their AWS machine learning skills, IT professionals interested in specializing in machine learning and cloud computing, students and graduates aspiring to build a career in these fields, and professionals seeking certification to pass the AWS Certified Machine Learning Engineer – Associate exam.

Enroll now: AWS Certified Machine Learning Engineer Associate Prep

Summary

Title: AWS Certified Machine Learning Engineer Associate Prep

Price: $44.99

Average Rating: 5

Number of Lectures: 24

Number of Published Lectures: 24

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: 19.99

Quality Status: approved

Status: Live

What You Will Learn

Introduction to AWS and Machine Learning

Data Engineering

Exploratory Data Analysis (EDA)

Machine Learning on AWS

Model Deployment and Monitoring

Machine Learning Frameworks

Deep Learning

AWS Machine Learning Services

Big Data and Machine Learning

Security and Compliance

Who Should Attend

This course is ideal for Data Scientists and Machine Learning Engineers looking to validate and enhance their AWS machine learning skills, IT professionals interested in specializing in machine learning and cloud computing, students and graduates aspiring to build a career in these fields, and professionals seeking certification to pass the AWS Certified Machine Learning Engineer – Associate exam.

Target Audiences

This course is ideal for Data Scientists and Machine Learning Engineers looking to validate and enhance their AWS machine learning skills, IT professionals interested in specializing in machine learning and cloud computing, students and graduates aspiring to build a career in these fields, and professionals seeking certification to pass the AWS Certified Machine Learning Engineer – Associate exam.

AWS Certified Machine Learning Engineer Associate Prep

Comprehensive Exam Prep for AWS Certified Machine Learning Engineer Associate – Anyone who is looking to pass this exam!

What is the AWS Certified Machine Learning Engineer – Associate Exam?

The AWS Certified Machine Learning Engineer – Associate exam validates your expertise in using AWS machine learning services to build, train, and deploy machine learning models. This course provides a comprehensive guide to prepare for this certification, covering all key topics and ensuring you’re ready to ace the exam.

Why is Passing This Exam Important?

Achieving the AWS Certified Machine Learning Engineer – Associate certification demonstrates your proficiency in machine learning and your ability to use AWS services effectively. It opens up numerous career opportunities and validates your skills to potential employers, making you a valuable asset in the tech industry.

Advantages of Learning for the Exam:

– Career Advancement: Enhance your resume with a highly respected certification.

– In-Depth Knowledge: Gain a comprehensive understanding of AWS machine learning services and best practices.

– Practical Skills: Learn to apply machine learning concepts using AWS tools, which are widely used in the industry.

Who Should Learn It:

– Data Scientists and Machine Learning Engineers: Looking to validate and enhance their AWS machine learning skills.

– IT Professionals: Interested in specializing in machine learning and cloud computing.

– Students and Graduates: Aspiring to build a career in machine learning and cloud technologies.

– Professionals Seeking Certification: Individuals aiming to pass the AWS Certified Machine Learning Engineer – Associate exam.

Basic Requirements:

Participants should have a basic understanding of machine learning concepts and some familiarity with AWS services. Prior experience in data science or related fields is beneficial but not mandatory. This course focuses on comprehensive exam preparation, including theoretical knowledge, without practical labs or hands-on implementation of cloud infrastructure.

Course Focus:

This course focuses on comprehensive exam preparation, including theoretical knowledge, to ensure readiness for the AWS Certified Machine Learning Engineer – Associate certification exam. It does not include practical labs or hands-on implementation of cloud infrastructure. By completing this course, students will be well-prepared to take the exam and advance their careers in machine learning and AWS.

Course Curriculum

Chapter 1: AWS Certified Machine Learning Engineer Associate Prep

Lecture 1: AWS Certified Machine Learning Engineer Associate Prep

Lecture 2: Getting Started with AWS EC2 S3 and RDS Overview

Lecture 3: Introduction to AWS Lambda VPC Elastic Beanstalk IAM and CloudFormation

Lecture 4: Core AWS Services Overview EC2 Lambda S3 Glacier RDS DynamoDB VPC Route 53

Lecture 5: AWS Management Tools – CloudWatch vs CloudTrail, Global Infra, Regions vs Zones

Lecture 6: AWS CDNs Global Accelerator Security Compliance IAM Policies Encryption KMS SSL

Lecture 7: AWS Compliance Programs Shield vs WAF Pricing Billing Models Marketplace

Lecture 8: AWS ML Fundamentals Basic Supervised Unsupervised Reinforcement

Lecture 9: AWS ML Training Data Validation Data Test Data Overfitting Underfitting

Lecture 10: AWS ML Bias-Variance Linear Regression Logistic Regression Decision Trees SVM

Lecture 11: AWS ML Neural Networks K-Means Hierarchical Clustering Model Evaluation Metrics

Lecture 12: AWS ML Accuracy Precision Recall F1-Score Confusion Matrix

Lecture 13: AWS ML ROC Curve AUC Feature Engineering Selection Data Preprocessing

Lecture 14: Normalization Standardization Feature Extraction Dimensionality Reduction

Lecture 15: AWS ML Model Monitoring Batch Prediction Real-Time Prediction A B Testing Perf

Lecture 16: AWS ML Data Engineering Data Collection Data Wrangling Data Storage Data Sec

Lecture 17: AWS ML EDA Data Visualization Statistical Analysis Feature Engineering

Lecture 18: AWS ML SageMaker SageMaker Studio Built-in Custom Algorithms Training Tuning

Lecture 19: AWS ML Endpoint Management Scaling Monitoring Models Debugging A B Testing

Lecture 20: AWS ML Frameworks TensorFlow PyTorch MxNet

Lecture 21: Deep Learning Neural Networks CNNs Image Recognition RNNs Sequence Data NLP

Lecture 22: AWS ML NLP Text Analysis Rekognition Image Video Analysis Polly Text-to-Speech

Lecture 23: AWS ML Lex Conversational Interfaces Glue Data Preparation ETL Kinesis Streaming

Lecture 24: AWS Big Data & ML EMR Processing Redshift Warehousing Data Pipeline Workflows

Instructors

Adrian Fischer
Instructor at Udemy

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5 stars: 18 votes

Frequently Asked Questions

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