kingers Posted Monday at 07:27 PM Report Share Posted Monday at 07:27 PM Aws Certified Machine Learning Specialty - Hands-On + Exams Published 8/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 11.08 GB | Duration: 23h 25mTheory | Hands-On Labs | Practice Questions | Downloadable PDF Slides | Pass the certification exam | Latest Syllabus What you'll learn Design and implement scalable ML data pipelines using AWS services like Kinesis, Glue, EMR, and Firehose for batch and streaming workloads Build, train, and optimize ML models using SageMaker with proper hyperparameter tuning, cross-validation, and evaluation metrics Deploy production ML solutions with AWS security best practices including IAM policies, VPC configuration, and data encryption Operationalize ML systems with monitoring, A/B testing, automated retraining pipelines, and performance optimization on AWS Requirements Basic understanding of machine learning concepts and Python programming is helpful, with AWS Machine Learning Associate certification providing a strong foundation but not required. You'll need an AWS free tier account for hands-on labs - all AWS services are explained from scratch with step-by-step demonstrations. Description Master AWS Machine Learning Services and Pass the MLS-C01 Certification ExamThis comprehensive course prepares you for the AWS Certified Machine Learning - Specialty (MLS-C01) certification exam through extensive content covering all essential AWS services. Aligned with the official AWS exam guide, the curriculum addresses all four certification domains: Data Engineering (20%), Exploratory Data Analysis (24%), Modeling (36%), and Machine Learning Implementation & Operations (20%).What You'll Learn:Through structured lectures combining theory and hands-on demonstrations, you'll master the complete ML lifecycle on AWS. Build data ingestion pipelines using Kinesis, Glue, and EMR. Design feature engineering solutions with proper data preprocessing and transformation techniques. Train and optimize models using SageMaker's built-in algorithms and custom implementations. Deploy production-ready ML solutions with comprehensive security, monitoring, and operational best practices.Course Structure:Each AWS service receives dedicated coverage with theoretical explanation followed by practical demonstration. Starting with foundational analytics services (Athena, Redshift, QuickSight), you'll progress through compute options (EC2, Lambda, Batch), containerization (ECS, EKS, Fargate), and dive deep into ML-specific services. The centerpiece SageMaker section covers end-to-end model development, while AI services like Comprehend, Rekognition, Transcribe, and Textract demonstrate pre-built ML capabilities.Hands-On Learning:A significant portion of the course consists of hands-on labs where you'll implement real solutions in the AWS console. Configure VPCs for secure ML environments, set up IAM policies for least-privilege access, implement CloudWatch monitoring for model performance, and build complete ML pipelines from data ingestion to model deployment. Every demonstration uses free-tier eligible services, ensuring you can follow along without significant costs.Exam Preparation:Beyond service knowledge, you'll understand key ML concepts required for certification: hyperparameter optimization, cross-validation, bias-variance tradeoffs, evaluation metrics (AUC-ROC, F1, precision/recall), and model selection criteria. Learn when to use built-in algorithms versus custom models, how to right-size infrastructure for cost optimization, and best practices for MLOps including A/B testing and automated retraining pipelines.Additional Resources:The course includes downloadable PDF slides for offline review, practice questions aligned with exam format, and reference materials for continued learning. Each section builds upon previous knowledge, creating a structured learning path from fundamentals to advanced implementations.Who Should Enroll:Perfect for data scientists, ML engineers, cloud architects, and developers pursuing AWS ML specialty certification. Whether advancing from AWS ML Associate certification or building on existing ML experience, this course provides both theoretical knowledge and practical skills needed for exam success and real-world implementation.Start your journey to becoming an AWS Certified Machine Learning Specialist today. Overview Section 1: Introduction Lecture 1 About The Instructor Lecture 2 Exam Strategy, Tips & Tricks Section 2: Analytics Lecture 3 Amazon Athena Lecture 4 Amazon Athena - Hands-On Demo Lecture 5 Amazon Data Firehose Lecture 6 Amazon EMR Lecture 7 Amazon EMR - Hands-On Demo Lecture 8 AWS Glue Lecture 9 AWS Glue - Hands-On Demo Lecture 10 Amazon Kinesis Data Streams Lecture 11 Amazon Kinesis Data Streams - Hands-On Demo Lecture 12 AWS Lake Formation Lecture 13 AWS Lake Formation - Hands-On Demo Lecture 14 Amazon Managed Service for Apache Flink Lecture 15 Amazon OpenSearch Service Lecture 16 Amazon OpenSearch Service - Hands-On Demo Lecture 17 Amazon QuickSight Lecture 18 Amazon QuickSight - Hands-On Demo Section 3: Compute Lecture 19 AWS Batch Lecture 20 AWS Batch - Hands-On Demo Lecture 21 Amazon EC2 Lecture 22 Amazon EC2 - Hands-On Demo Lecture 23 AWS Lambda Lecture 24 AWS Lambda - Hands-On Demo Section 4: Containers Lecture 25 Amazon Elastic Container Registry (Amazon ECR) Lecture 26 Amazon Elastic Container Registry (Amazon ECR) - Hands-On Demo Lecture 27 Amazon Elastic Container Service (Amazon ECS) Lecture 28 Amazon Elastic Container Service (Amazon ECS) - Hands-On Demo Lecture 29 Amazon Elastic Kubernetes Service (Amazon EKS) Lecture 30 Amazon Elastic Kubernetes Service (Amazon EKS) - Hands-On Demo Lecture 31 AWS Fargate Section 5: Database Lecture 32 Amazon Redshift Lecture 33 Amazon Redshift - Hands-On Demo Section 6: Internet of Things Lecture 34 AWS IoT Greengrass Section 7: Machine Learning Lecture 35 Amazon Bedrock Lecture 36 Amazon Bedrock - Hands-On Demo Lecture 37 Amazon Comprehend Lecture 38 Amazon Comprehend - Hands-On Demo Lecture 39 Amazon Forecast Lecture 40 Amazon Fraud Detector Lecture 41 Amazon Fraud Detector - Hands-On Demo Lecture 42 Amazon Lex Lecture 43 Amazon Lex - Hands-On Demo Lecture 44 Amazon Kendra Lecture 45 Amazon Kendra - Hands-On Demo Lecture 46 Amazon Polly Lecture 47 Amazon Polly - Hands-On Demo Lecture 48 Amazon Rekognition Lecture 49 Amazon Rekognition - Hands-On Demo Lecture 50 Amazon SageMaker Lecture 51 Amazon SageMaker - Hands-On Demo Lecture 52 Amazon Textract Lecture 53 Amazon Textract - Hands-On Demo Lecture 54 Amazon Transcribe Lecture 55 Amazon Transcribe - Hands-On Demo Lecture 56 Amazon Translate Lecture 57 Amazon Translate - Hands-On Demo Section 8: Management and Governance Lecture 58 AWS CloudTrail Lecture 59 AWS CloudTrail - Hands-On Demo Lecture 60 Amazon CloudWatch Lecture 61 Amazon CloudWatch - Hands-On Demo Section 9: Networking and Content Delivery Lecture 62 Amazon VPC - Part 1 Lecture 63 Amazon VPC - Part 2 Lecture 64 Amazon VPC - Hands-On Demo Section 10: Security, Identity, and Compliance Lecture 65 AWS Identity and Access Management (IAM) - Part 1 Lecture 66 AWS Identity and Access Management (IAM) - Part 2 Lecture 67 AWS Identity and Access Management (IAM) - Hands-On Demo Section 11: Storage Lecture 68 Amazon Elastic Block Store (Amazon EBS) Lecture 69 Amazon Elastic Block Store (Amazon EBS) - Hands-On Demo Lecture 70 Amazon Elastic File System (Amazon EFS) Lecture 71 Amazon Elastic File System (Amazon EFS) - Hands-On Demo Lecture 72 Amazon FSx Lecture 73 Amazon Simple Storage Service (S3) - Part 1 Lecture 74 Amazon Simple Storage Service (S3) - Part 2 Lecture 75 Amazon Simple Storage Service (S3) - Part 3 Lecture 76 Amazon Simple Storage Service (S3) - Part 4 Lecture 77 Amazon S3 Hands-On Demo Section 12: Practice Exam Data scientists, ML engineers, and cloud professionals preparing for the AWS Certified Machine Learning - Specialty (MLS-C01) exam, or anyone with AWS ML Associate certification ready to advance. Also suitable for developers and IT professionals transitioning to MLOps roles who need hands-on experience with AWS's complete ML ecosystem.RapidGatorhttps://rapidgator.net/file/5ac82389f265a89ea52d52ca89be2103/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part1.rarhttps://rapidgator.net/file/950d8da64c575480e0147f2d0ea50e37/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part2.rarhttps://rapidgator.net/file/d5f44d3d2d5b1891c6da2432a1ddad22/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part3.rarhttps://rapidgator.net/file/ce854d694323fff6cb77c9a336775615/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part4.rarNitroFlarehttps://nitroflare.com/view/3138E0EECC5C5CD/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part1.rarhttps://nitroflare.com/view/E8CC0193F8FAA26/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part2.rarhttps://nitroflare.com/view/00BCAB7BDE8FB46/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part3.rarhttps://nitroflare.com/view/21A1F36B85BBCAD/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part4.rarDDownloadhttps://ddownload.com/pvk91nvagep3/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part1.rarhttps://ddownload.com/mhlgsy4ybymt/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part2.rarhttps://ddownload.com/8auxyrbjudbq/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part3.rarhttps://ddownload.com/2fta12ied9oi/yxusj.Udemy.-.AWS.Certified.Machine.Learning.Specialty.2025.-.Hands.On.part4.rar Link to comment Share on other sites More sharing options...
Recommended Posts
Please sign in to comment
You will be able to leave a comment after signing in
Sign In Now