Aws Certified Machine Learning Specialty Mls-C01

[2024] Ace your AWS Certified Machine Learning Specialty Exam [MLS-C01] | AWS Machine Learning Practice Test included

What you'll learn

12 HOURS OF INSTRUCTOR-GUIDED LECTURES: Learn how to design, build, deploy, optimize, train, tune, and maintain ML solutions using AWS services

PRACTICE EXAM: Exam-Difficulty practice exam included to test your progress and knowledge

ACTIVE Q&A FORUM: Our discussion board provides a platform for students to ask questions, share their recent exam experiences, and offer feedback on exam topics

RESPONSIVE SUPPORT: Our team of AWS experts respond to all of your questions, concerns or feedback

ALWAYS UP TO DATE: Our teachings reflect the latest MLS-C01 exam. Students have lifetime access to all future updates

PRESENTED IN A PROFESSIONAL WAY: Focused and to the point, clear language with professional subtitles

THE ULTIMATE EXAM PREP: We’ll teach you everything you need to know to ace your AWS certification exam

Requirements

This course is designed for individuals with a solid AWS knowledge and experience (at the Associate level)

A free-tier AWS account is recommended to follow along with the practice labs - we’ll show you step by step how to create one

To assess your exam readiness, we highly recommend enrolling in the AWS Certified Machine Learning Specialty practice exam course by Neal Davis

Description

Are you ready to take your AWS Machine Learning knowledge to the next level and earn your AWS Certified Machine Learning Specialty certification? Then this AWS Machine Learning Specialty video course is for you! Designed for intermediate to advanced learners, this 12-hour training will equip you with the knowledge and confidence you need to succeed in your MLS-C01 exam.You will gain a deep level of knowledge and expertise in AWS Machine Learning with the help of:12 hours of comprehensive video lessonsDetailed presentations and diagramsResources available for download - including code and slidesA complimentary practice exam to test your knowledgeA supportive community of students and instructorsThis course is your key to acing the Certified Machine Learning Specialty exam! With our mixture of in-depth theory, architectural diagrams and hands-on training, you'll learn how to design, build, deploy, optimize, train, tune, and maintain ML solutions using AWS services. With this comprehensive Udemy AWS Machine Learning Specialty training, you have everything you need to comfortably pass the MLS-C01 certification exam.PREVIEW THIS COURSEWatch the intro video to find out why students choose Digital Cloud Training to prepare for their AWS exams.With our FREE previews you can see for yourself how we prepare you for the AWS Certified Machine Learning [MLS-C01] exam using guided AWS hands-on lessons. Check out the curriculum to see the vast amount of practical exercises combined with in-depth theoretical training.TOP REASONS WHY THIS ULTIMATE EXAM PREP IS YOUR BEST CHANCE TO ACE YOUR AWS EXAMTHE ULTIMATE EXAM PREP: We’ll teach you everything you need to know (in theory and practice) to pass your exam on your first attemptGUIDED HANDS-ON LESSONS: The many hands-on lessons are backed by high-quality logical diagrams so you can visualize what you're buildingBONUS PRACTICE TEST: Our practice test is timed and scored mimicking the real exam environment so you get familiar with the real AWS exam format, style and difficultyDETAILED EXPLANATIONS: Every question includes deep-dive reference links and detailed explanations that describe why each answer is correct or incorrectHIGH-QUALITY VISUALS: We've spared no effort to create a highly visual training course with lots of tables and graphs to illustrate the conceptsPRESENTED IN A PROFESSIONAL WAY: Your instructors use clear and easy to understand language and present the material in a professional way - focused and to the point with professional subtitlesCERTIFICATE OF COMPLETION: Upon course completion, you get to download your Certificate of Completion issued by UdemyACCESS DIAGRAMS, CODE AND SLIDES: Diagrams, code and slides (optional, requires name/email) presented throughout the course are available for download in PDF formatRESPONSIVE SUPPORT: Our team of AWS experts comprehensively respond to all of your questions, concerns or feedbackACTIVE Q&A DISCUSSION BOARD: Join the discussion on AWS related topics in our discussion forum where our students share their recent exam experience offering feedback on which topics were coveredMOBILE ACCESS: Study on the go and access all resources from your mobile phone - anywhere, anytimeLIFETIME ACCESS: All students have lifetime access to all future updates of this courseYOUR INSTRUCTORSKARIM ELKOBROSSYAWS COMMUNITY BUILDER (ML), AWS CERTIFIED AND MACHINE LEARNING INSTRUCTOR & AUTHORHi, my name is Karim – I’ll be your lead instructor for this AWS Certified Machine Learning Specialty training. I am an Electromechanical engineer with a passion for AI. Together with Neal, we created this comprehensive AWS training so that you get to ace your AWS Machine Learning exam and achieve your career goals. NEAL DAVISFOUNDER OF DIGITAL CLOUD TRAINING, AWS SOLUTION ARCHITECT, BEST-SELLING AUTHOR & IT INSTRUCTORHi, I'm Neal Davis, and I'm delighted to be your co-instructor for this course. As the founder of Digital Cloud Training, I'm deeply committed to providing top-quality AWS certification training resources. With over 20 years of hands-on experience in the Cloud space, I'm excited to share my expertise with you on Udemy.OUR SUCCESS IN NUMBERSOver 500,000 students enrolled in our AWS courses on Udemy4.7 Star instructor ratings from over 100,000 reviewsOur students pass the AWS exam with an average score of over 85%MONEY-BACK GUARANTEEWe are totally confident in the value of our AWS Machine Learning course which comes with a 30-day money-back guarantee (no questions asked). Fast-track your AWS exam success and get lifetime access now - risk-free!ENROLL NOWTake the first step towards advancing your cloud career and becoming AWS Certified Machine Learning Specialist!By enrolling in this video course, you will not only pass the AWS Certified Machine Learning Specialty exam but also deepen your understanding of Machine Learning. Enhance your knowledge and set yourself apart in the industry by taking this MLS-C01 exam preparation course.

Overview

Section 1: Let's Get Started!

Lecture 1 How to Use this Course

Lecture 2 The MLS-C01 Exam

Lecture 3 Course Download

Section 2: AWS Accounts and IAM

Lecture 4 Introduction

Lecture 5 AWS Account Overview

Lecture 6 [HOL] Create Your AWS Free Tier Account

Lecture 7 [HOL] Configure Account and Create a Billing Alarm

Lecture 8 AWS IAM Overview

Lecture 9 IAM Users, Groups, Roles and Policies

Lecture 10 [HOL] Create IAM User Account

Section 3: Compute, Storage, and Database

Lecture 11 Introduction

Lecture 12 Amazon Elastic Compute Cloud (EC2)

Lecture 13 Amazon Elastic Container Service (ECS)

Lecture 14 Amazon S3 Overview

Lecture 15 IAM Policies, Bucket Policies and ACLs

Lecture 16 Block vs File vs Object Storage

Lecture 17 Amazon EBS

Lecture 18 Amazon Elastic File System (EFS)

Lecture 19 Amazon FSx

Lecture 20 Amazon DynamoDB

Lecture 21 Amazon Redshift

Section 4: Data Engineering

Lecture 22 Introduction

Lecture 23 Amazon Kinesis

Lecture 24 Amazon Kinesis Data Streams

Lecture 25 [HOL] Create a Kinesis Data Stream

Lecture 26 Amazon Kinesis Data Firehose

Lecture 27 [HOL] Create a Kinesis Data Firehose

Lecture 28 Kinesis Data Streams vs Firehose

Lecture 29 Amazon Kinesis Data Analytics

Lecture 30 Amazon Kinesis Video Streams

Lecture 31 AWS Glue

Lecture 32 [HOL] AWS Glue (crawler + transformation)

Lecture 33 AWS Batch

Lecture 34 AWS Database Migration Service (DMS)

Lecture 35 AWS Step Functions

Lecture 36 Exam cram

Section 5: Exploratory Data Analysis

Lecture 37 Introduction

Lecture 38 Cross-Industry Standard Process for Data Mining (CRISP-DM)

Lecture 39 Plots

Lecture 40 Data types

Lecture 41 Data distribution

Lecture 42 Feature Engineering

Lecture 43 Data transformation (Numbers-Categories)

Lecture 44 Data transformation (Text-Images)

Lecture 45 Imputation Techniques

Lecture 46 Unbalanced data

Lecture 47 Outliers

Lecture 48 Amazon Sagemaker Ground Truth

Lecture 49 [HOL] Create a labelling job

Lecture 50 Amazon Quicksight

Lecture 51 [HOL] Create an analysis using Quicksight

Lecture 52 Amazon Athena

Lecture 53 [HOL] Running SQL queries in Athena

Lecture 54 Amazon Elastic Map Reduce (EMR)

Lecture 55 Exam cram

Section 6: Machine learning

Lecture 56 Introduction

Lecture 57 Machine Learning categories

Lecture 58 Regression

Lecture 59 Regression - Model evaluation

Lecture 60 Classification

Lecture 61 Classification - Model evaluation

Lecture 62 Dimensionality Reduction

Lecture 63 Deep Learning

Lecture 64 Natural Language processing (NLP)

Lecture 65 Computer Vision (CV)

Lecture 66 Convolutional Neural Network (CNN)

Lecture 67 Recurrent Neural Network

Lecture 68 Advancements in NLP

Lecture 69 Neural Network characteristics

Lecture 70 Neural Networks' problems

Lecture 71 Overfitting/Underfitting

Lecture 72 Preventing overfitting

Lecture 73 Validation techniques

Lecture 74 Decision Trees

Lecture 75 Ensemble learning

Lecture 76 Exam cram

Section 7: AI services

Lecture 77 Introduction

Lecture 78 AI services

Lecture 79 Amazon Comprehend

Lecture 80 [HOL] Customer's reviews sentiment analysis

Lecture 81 Amazon Translate

Lecture 82 Amazon Transcribe

Lecture 83 Amazon Polly

Lecture 84 Amazon Rekognition

Lecture 85 [HOL] Amazon Rekognition

Lecture 86 AWS Deeplens

Lecture 87 AWS Panorama

Lecture 88 Amazon Textract

Lecture 89 Amazon Forecast

Lecture 90 Amazon Lex

Lecture 91 Amazon Fraud detector

Lecture 92 Amazon Personalize

Lecture 93 Amazon Kendra

Lecture 94 [HOL] Amazon Kendra

Lecture 95 Exam cram

Section 8: Modelling

Lecture 96 Introduction

Lecture 97 Amazon SageMaker

Lecture 98 [HOL] Amazon SageMaker Walkthrough

Lecture 99 [HOL] Create an Amazon SageMaker Notebook instance

Lecture 100 Built-in algorithms overview

Lecture 101 Linear Learner

Lecture 102 XGBoost

Lecture 103 K-Nearest Neighbours

Lecture 104 Factorization machines

Lecture 105 DeepAR

Lecture 106 Image classification

Lecture 107 Object Detection

Lecture 108 Semantic Segmentation

Lecture 109 Seq2Seq

Lecture 110 BLazingText

Lecture 111 Neural Topic Model (NTM)

Lecture 112 Latent Dirichlet Allocation (LDA)

Lecture 113 Random Cut Forest (RCF)

Lecture 114 K-means clustering

Lecture 115 Hierarchical clustering

Lecture 116 Object2Vec

Lecture 117 Principal Component Analysis (PCA)

Lecture 118 IP insights

Lecture 119 Reinforcement learning

Lecture 120 Built-in algorithms recap

Lecture 121 SageMaker Data Wrangler

Lecture 122 [HOL] SageMaker Data Wrangler

Lecture 123 SageMaker Canvas

Lecture 124 [HOL] SageMaker Canvas

Lecture 125 Bias in Machine Learning

Lecture 126 Amazon SageMaker Clarify

Lecture 127 Amazon SageMaker Feature Store

Lecture 128 Amazon SageMaker ML Lineage Tracking

Lecture 129 Docker containers with Sagemaker

Lecture 130 [HOL] XGBoost (Churn prediction)

Lecture 131 Hugging Face with SageMaker

Lecture 132 [HOL] Hugging Face with SageMaker

Lecture 133 [HOL] Script mode

Lecture 134 [HOL] Bring Your Own (BYO) Docker

Lecture 135 Sagemaker Instance types

Lecture 136 Hyperparameter tuning

Lecture 137 [HOL] Hyperparameter tuning job

Lecture 138 Distributed Training

Lecture 139 Apache Spark with Sagemaker

Lecture 140 Sagemaker Debugger

Lecture 141 Sagemaker Autopilot

Lecture 142 Exam cram

Section 9: Deployment

Lecture 143 Introduction

Lecture 144 Online Inference (Real-time)

Lecture 145 Batch transform

Lecture 146 Sagemaker Deployment

Lecture 147 SageMaker MLOps for Kubernetes and SageMaker Projects

Lecture 148 AWS Neuron

Lecture 149 Torchserve

Lecture 150 Amazon SageMaker Inference Recommender

Lecture 151 Amazon SageMaker Serverless Inference

Lecture 152 Inference Pipeline

Lecture 153 SageMaker Monitoring

Lecture 154 Sagemaker Security

Lecture 155 Sagemaker Model Monitor

Lecture 156 Sagemaker Neo and IOT greengrass

Lecture 157 EC2 Inf1 instances

Lecture 158 AWS Inferentia

Lecture 159 [HOL] XGBoost (Churn prediction) deployment

Lecture 160 Exam cram

Section 10: Practice Test

Section 11: Additional Training

Lecture 161 Bonus Lesson

Individuals preparing for the AWS Machine Learning Specialty certification exam who want to pass with confidence,Professionals seeking to expand their skillset in AI and ML or those who want to transition into a data-driven career in cloud computing,Students who want to enhance their skills by learning how to implement machine learning solutions on the AWS platform,AI practitioners seeking to broaden their expertise in implementing, deploying, and managing ML solutions on AWS for a scalable and cost-effective approach,Programmers interested in incorporating machine learning techniques into their applications, allowing them to create more intelligent and data-driven software solutions,Technical leaders and executives looking to understand the capabilities and benefits of AWS Machine Learning services to make informed decisions on adopting and implementing ML solutions in their organizations,Anyone who is keen to take their career and salary to the next level with an AWS certification