About Course

AWS Certified Machine Learning – Specialty Exam (MLS-C01) Prep Course – FREE!

This comprehensive course, taught by industry experts Frank Kane and Stephane Maarek, prepares you for the challenging AWS Certified Machine Learning – Specialty exam. It covers all four domains tested in the exam, including data engineering, exploratory data analysis, modeling, and machine learning implementation and operations.

Get hands-on experience with four labs, and learn about cutting-edge technology like generative AI (GPT), Bedrock, SageMaker JumpStart for Generative AI, CodeWhisperer, and SageMaker Foundation Models. The course is packed with information on essential AWS services, including:

S3 data lakes
AWS Glue and Glue ETL
Kinesis data streams, firehose, and video streams
DynamoDB
Data Pipelines, AWS Batch, and Step Functions
scikit-learn
Athena and Quicksight
Elastic MapReduce (EMR)
Apache Spark and MLLib
Feature engineering (imputation, outliers, binning, transforms, encoding, and normalization)
Ground Truth
Deep Learning basics
Tuning neural networks and avoiding overfitting
Amazon SageMaker, including SageMaker Studio, SageMaker Model Monitor, SageMaker Autopilot, and SageMaker Debugger
Regularization techniques
Evaluating machine learning models (precision, recall, F1, confusion matrix, etc.)
High-level ML services: Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more
Building recommender systems with Amazon Personalize
Monitoring industrial equipment with Lookout and Monitron
Security best practices with machine learning on AWS

This course is available for free and comes with lifetime access to all future updates, a responsive instructor in the Q&A section, and a Udemy Certificate of Completion. This course is ideal for individuals with associate-level AWS certification and some real-world industry experience. Don’t miss out on this opportunity to gain a competitive edge in the field of machine learning. Enroll today!

This course is completely free!

This course is available on Udemy, Udacity, Coursera, MasterClass, NearPeer, and other popular platforms.

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

Course Content

01 – Introduction

A Message from the Professor
001 Udemy 101.mp4

00:00
002 Course Introduction What to Expect.mp4

00:00
003 Get the Course Materials.mp4

00:00
external-links.txt

00:00
Section Quiz

02 – Data Engineering

001 Section Intro Data Engineering.mp4

00:00
002 Amazon S3 – Overview.mp4

00:00
003 Amazon S3 Storage Classes + Glacier.mp4

00:00
004 Amazon S3 Storage + Glacier – Hands On.mp4

00:00
005 Amazon S3 Lifecycle Rules.mp4

00:00
006 Amazon S3 Lifecycle Rules – Hands On.mp4

00:00
007 Amazon S3 Security.mp4

00:00
008 Kinesis Data Streams & Kinesis Data Firehose.mp4

00:00
009 Lab 1.1 – Kinesis Data Firehose.mp4

00:00
010 Kinesis Data Analytics.mp4

00:00
011 Lab 1.2 – Kinesis Data Analytics.mp4

00:00
012 Kinesis Video Streams.mp4

00:00
013 Kinesis ML Summary.mp4

00:00
014 Glue Data Catalog & Crawlers.mp4

00:00
015 Lab 1.3 – Glue Data Catalog.mp4

00:00
016 Glue ETL.mp4

00:00
017 Lab 1.4 – Glue ETL.mp4

00:00
018 Lab 1.5 – Athena.mp4

00:00
019 Lab 1 – Cleanup.mp4

00:00
020 AWS Data Stores in Machine Learning.mp4

00:00
021 AWS Data Pipelines.mp4

00:00
022 AWS Batch.mp4

00:00
023 AWS DMS – Database Migration Services.mp4

00:00
024 AWS Step Functions.mp4

00:00
025 Full Data Engineering Pipelines.mp4

00:00
026 Data Engineering Summary.html

00:00
Section Quiz

03 – Exploratory Data Analysis

001 Section Intro Data Analysis.mp4

00:00
002 Python in Data Science and Machine Learning.mp4

00:00
003 Example Preparing Data for Machine Learning in a Jupyter Notebook.mp4

00:00
004 Types of Data.mp4

00:00
005 Data Distributions.mp4

00:00
006 Time Series Trends and Seasonality.mp4

00:00
007 Introduction to Amazon Athena.mp4

00:00
008 Overview of Amazon Quicksight.mp4

00:00
009 Types of Visualizations, and When to Use Them.mp4

00:00
010 Elastic MapReduce (EMR) and Hadoop Overview.mp4

00:00
011 Apache Spark on EMR.mp4

00:00
012 EMR Notebooks, Security, and Instance Types.mp4

00:00
013 Feature Engineering and the Curse of Dimensionality.mp4

00:00
014 Imputing Missing Data.mp4

00:00
015 Dealing with Unbalanced Data.mp4

00:00
016 Handling Outliers.mp4

00:00
017 Binning, Transforming, Encoding, Scaling, and Shuffling.mp4

00:00
018 Amazon SageMaker Ground Truth and Label Generation.mp4

00:00
019 Lab Preparing Data for TF-IDF with Spark and EMR, Part 1.mp4

00:00
020 Lab Preparing Data for TF-IDF with Spark and EMR, Part 2.mp4

00:00
021 Lab Preparing Data for TF-IDF with Spark and EMR, Part 3.mp4

00:00
Section Quiz

04 – Modeling, Part 1 General Deep Learning and Machine Learning

001 Section Intro Modeling.mp4

00:00
002 Introduction to Deep Learning.mp4

00:00
003 Activation Functions.mp4

00:00
004 Convolutional Neural Networks.mp4

00:00
005 Recurrent Neural Networks.mp4

00:00
006 Deep Learning on EC2 and EMR.mp4

00:00
007 Tuning Neural Networks.mp4

00:00
008 Regularization Techniques for Neural Networks (Dropout, Early Stopping).mp4

00:00
009 L1 and L2 Regularization.mp4

00:00
010 Grief with Gradients The Vanishing Gradient problem.mp4

00:00
011 The Confusion Matrix.mp4

00:00
012 Precision, Recall, F1, AUC, and more.mp4

00:00
013 Ensemble Methods Bagging and Boosting.mp4

00:00
Section Quiz

05 – Modeling, Part 2 Amazon SageMaker

001 Introducing Amazon SageMaker.mp4

00:00
002 Linear Learner in SageMaker.mp4

00:00
003 XGBoost in SageMaker.mp4

00:00
004 Seq2Seq in SageMaker.mp4

00:00
005 DeepAR in SageMaker.mp4

00:00
006 BlazingText in SageMaker.mp4

00:00
007 Object2Vec in SageMaker.mp4

00:00
008 Object Detection in SageMaker.mp4

00:00
009 Image Classification in SageMaker.mp4

00:00
010 Semantic Segmentation in SageMaker.mp4

00:00
011 Random Cut Forest in SageMaker.mp4

00:00
012 Neural Topic Model in SageMaker.mp4

00:00
013 Latent Dirichlet Allocation (LDA) in SageMaker.mp4

00:00
014 K-Nearest-Neighbors (KNN) in SageMaker.mp4

00:00
015 K-Means Clustering in SageMaker.mp4

00:00
016 Principal Component Analysis (PCA) in SageMaker.mp4

00:00
017 Factorization Machines in SageMaker.mp4

00:00
018 IP Insights in SageMaker.mp4

00:00
019 Reinforcement Learning in SageMaker.mp4

00:00
020 Automatic Model Tuning.mp4

00:00
021 Apache Spark with SageMaker.mp4

00:00
022 SageMaker Studio, and SageMaker Experiments.mp4

00:00
023 SageMaker Debugger.mp4

00:00
024 SageMaker Autopilot AutoML.mp4

00:00
025 SageMaker Model Monitor.mp4

00:00
026 Other recent features (JumpStart, Data Wrangler, Features Store, Edge Manager).mp4

00:00
027 SageMaker Canvas.mp4

00:00
028 SageMaker Training Compiler.mp4

00:00
Section Quiz

06 – Modeling, Part 3 High-Level ML Services

001 Amazon Comprehend.mp4

00:00
002 Amazon Translate.mp4

00:00
003 Amazon Transcribe.mp4

00:00
004 Amazon Polly.mp4

00:00
005 Amazon Rekognition.mp4

00:00
006 Amazon Forecast.mp4

00:00
007 Amazon Lex.mp4

00:00
008 Amazon Personalize.mp4

00:00
009 Lightning round! TexTract, DeepLens, DeepRacher, Lookout, and Monitron.mp4

00:00
010 TorchServe, AWS Neuron, and AWS Panorama.mp4

00:00
011 Deep Composer, Fraud Detection, CodeGuru, and Contact Lens.mp4

00:00
012 Amazon Kendra and Amazon Augmented AI (A2I).mp4

00:00
Section Quiz

07 – Modeling, Part 4 Wrapping up & Lab Activity

08 – ML Implementation and Operations

001 Section Intro Machine Learning Implementation and Operations.mp4

00:00
002 SageMaker’s Inner Details and Production Variants.mp4

00:00
003 SageMaker On the Edge SageMaker Neo and IoT Greengrass.mp4

00:00
004 SageMaker Security Encryption at Rest and In Transit.mp4

00:00
005 SageMaker Security VPC’s, IAM, Logging, and Monitoring.mp4

00:00
006 SageMaker Resource Management Instance Types and Spot Training.mp4

00:00
007 SageMaker Resource Management Elastic Inference, Automatic Scaling, AZ’s.mp4

00:00
008 SageMaker Serverless Inference and Inference Recommender.mp4

00:00
009 SageMaker Inference Pipelines.mp4

00:00
010 Lab Tuning, Deploying, and Predicting with Tensorflow on SageMaker – Part 1.mp4

00:00
011 Lab Tuning, Deploying, and Predicting with Tensorflow on SageMaker – Part 2.mp4

00:00
012 Lab Tuning, Deploying, and Predicting with Tensorflow on SageMaker – Part 3.mp4

00:00
Section Quiz

09 – Wrapping Up

10 – Practice Exams

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Student Ratings & Reviews

5.0

Total 1 Rating

1 Rating

0 Rating

SAYIQA JABEEN

3 months ago

All is great but also include coding lecture

About Course

AWS Certified Machine Learning – Specialty Exam (MLS-C01) Prep Course – FREE!

What Will You Learn?

Course Content

01 – Introduction

A Message from the Professor

001 Udemy 101.mp4

002 Course Introduction What to Expect.mp4

003 Get the Course Materials.mp4

external-links.txt

Section Quiz

02 – Data Engineering

001 Section Intro Data Engineering.mp4

002 Amazon S3 – Overview.mp4

003 Amazon S3 Storage Classes + Glacier.mp4

004 Amazon S3 Storage + Glacier – Hands On.mp4

005 Amazon S3 Lifecycle Rules.mp4

006 Amazon S3 Lifecycle Rules – Hands On.mp4

007 Amazon S3 Security.mp4

008 Kinesis Data Streams & Kinesis Data Firehose.mp4

009 Lab 1.1 – Kinesis Data Firehose.mp4

010 Kinesis Data Analytics.mp4

011 Lab 1.2 – Kinesis Data Analytics.mp4

012 Kinesis Video Streams.mp4

013 Kinesis ML Summary.mp4

014 Glue Data Catalog & Crawlers.mp4

015 Lab 1.3 – Glue Data Catalog.mp4

016 Glue ETL.mp4

017 Lab 1.4 – Glue ETL.mp4

018 Lab 1.5 – Athena.mp4

019 Lab 1 – Cleanup.mp4

020 AWS Data Stores in Machine Learning.mp4

021 AWS Data Pipelines.mp4

022 AWS Batch.mp4

023 AWS DMS – Database Migration Services.mp4

024 AWS Step Functions.mp4

025 Full Data Engineering Pipelines.mp4

026 Data Engineering Summary.html

Section Quiz

03 – Exploratory Data Analysis

001 Section Intro Data Analysis.mp4

002 Python in Data Science and Machine Learning.mp4

003 Example Preparing Data for Machine Learning in a Jupyter Notebook.mp4

004 Types of Data.mp4

005 Data Distributions.mp4

006 Time Series Trends and Seasonality.mp4

007 Introduction to Amazon Athena.mp4

008 Overview of Amazon Quicksight.mp4

009 Types of Visualizations, and When to Use Them.mp4

010 Elastic MapReduce (EMR) and Hadoop Overview.mp4

011 Apache Spark on EMR.mp4

012 EMR Notebooks, Security, and Instance Types.mp4

013 Feature Engineering and the Curse of Dimensionality.mp4

014 Imputing Missing Data.mp4

015 Dealing with Unbalanced Data.mp4

016 Handling Outliers.mp4

017 Binning, Transforming, Encoding, Scaling, and Shuffling.mp4

018 Amazon SageMaker Ground Truth and Label Generation.mp4

019 Lab Preparing Data for TF-IDF with Spark and EMR, Part 1.mp4

020 Lab Preparing Data for TF-IDF with Spark and EMR, Part 2.mp4

021 Lab Preparing Data for TF-IDF with Spark and EMR, Part 3.mp4

Section Quiz

04 – Modeling, Part 1 General Deep Learning and Machine Learning

001 Section Intro Modeling.mp4

002 Introduction to Deep Learning.mp4

003 Activation Functions.mp4

004 Convolutional Neural Networks.mp4

005 Recurrent Neural Networks.mp4

006 Deep Learning on EC2 and EMR.mp4

007 Tuning Neural Networks.mp4

008 Regularization Techniques for Neural Networks (Dropout, Early Stopping).mp4

009 L1 and L2 Regularization.mp4

010 Grief with Gradients The Vanishing Gradient problem.mp4

011 The Confusion Matrix.mp4

012 Precision, Recall, F1, AUC, and more.mp4

013 Ensemble Methods Bagging and Boosting.mp4

Section Quiz

05 – Modeling, Part 2 Amazon SageMaker

001 Introducing Amazon SageMaker.mp4

002 Linear Learner in SageMaker.mp4