Certification training

AWS-Certified-Machine-Learning-Specialty-MLS-C01AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01)

Prepare for your Amazon AWS exam with a structured video course built for focused study, topic review, and repeatable progress before exam day.

106Lectures
9h 8mDuration
Amazon AWSVendor
AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01) course cover Best seller
Amazon AWS certification training AWS-Certified-Machine-Learning-Specialty-MLS-C01 106 lessons arranged in a guided course path
Course overview

Study with a clear path.

Move through focused sections, review lecture timing, and return directly to the objectives that need more work.

Sequenced lessons

Follow the course in order or jump directly to the section you need to revisit.

Video-first prep

Use concise lecture blocks for technical review before moving into exam practice.

Fast access

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Curriculum

Course sections.

6 sections, 106 lessons, and lecture-level duration details.

01 Course Introduction: What to Expect 6m

01 Section Intro: Data Engineering 1m
02 Amazon S3 - Overview 5m
03 Amazon S3 - Storage Tiers & Lifecycle Rules 4m
04 Amazon S3 Security 8m
05 Kinesis Data Streams & Kinesis Data Firehose 9m
06 Lab 1.1 - Kinesis Data Firehose 6m
07 Kinesis Data Analytics 4m
08 Lab 1.2 - Kinesis Data Analytics 7m
09 Kinesis Video Streams 3m
10 Kinesis ML Summary 1m
11 Glue Data Catalog & Crawlers 3m
12 Lab 1.3 - Glue Data Catalog 4m
13 Glue ETL 2m
14 Lab 1.4 - Glue ETL 6m
15 Lab 1.5 - Athena 1m
16 Lab 1 - Cleanup 2m
17 AWS Data Stores in Machine Learning 3m
18 AWS Data Pipelines 3m
19 AWS Batch 2m
20 AWS DMS - Database Migration Services 2m
21 AWS Step Functions 3m
22 Full Data Engineering Pipelines 5m

01 Section Intro: Data Analysis 1m
02 Python in Data Science and Machine Learning 12m
03 Example: Preparing Data for Machine Learning in a Jupyter Notebook. 10m
04 Types of Data 5m
05 Data Distributions 6m
06 Time Series: Trends and Seasonality 4m
07 Introduction to Amazon Athena 5m
08 Overview of Amazon Quicksight 6m
09 Types of Visualizations, and When to Use Them. 5m
10 Elastic MapReduce (EMR) and Hadoop Overview 7m
11 Apache Spark on EMR 10m
12 EMR Notebooks, Security, and Instance Types 4m
13 Feature Engineering and the Curse of Dimensionality 7m
14 Imputing Missing Data 8m
15 Dealing with Unbalanced Data 6m
16 Handling Outliers 9m
17 Binning, Transforming, Encoding, Scaling, and Shuffling 8m
18 Amazon SageMaker Ground Truth and Label Generation 4m
19 Lab: Preparing Data for TF-IDF with Spark and EMR, Part 1 6m
20 Lab: Preparing Data for TF-IDF with Spark and EMR, Part 2 10m
21 Lab: Preparing Data for TF-IDF with Spark and EMR, Part 3 14m

01 Section Intro: Modeling 2m
02 Introduction to Deep Learning 9m
03 Convolutional Neural Networks 12m
04 Recurrent Neural Networks 11m
05 Deep Learning on EC2 and EMR 2m
06 Tuning Neural Networks 5m
07 Regularization Techniques for Neural Networks (Dropout, Early Stopping) 7m
08 Grief with Gradients: The Vanishing Gradient problem 4m
09 L1 and L2 Regularization 3m
10 The Confusion Matrix 6m
11 Precision, Recall, F1, AUC, and more 7m
12 Ensemble Methods: Bagging and Boosting 4m
13 Introducing Amazon SageMaker 8m
14 Linear Learner in SageMaker 5m
15 XGBoost in SageMaker 3m
16 Seq2Seq in SageMaker 5m
17 DeepAR in SageMaker 4m
18 BlazingText in SageMaker 5m
19 Object2Vec in SageMaker 5m
20 Object Detection in SageMaker 4m
21 Image Classification in SageMaker 4m
22 Semantic Segmentation in SageMaker 4m
23 Random Cut Forest in SageMaker 3m
24 Neural Topic Model in SageMaker 3m
25 Latent Dirichlet Allocation (LDA) in SageMaker 3m
26 K-Nearest-Neighbors (KNN) in SageMaker 3m
27 K-Means Clustering in SageMaker 5m
28 Principal Component Analysis (PCA) in SageMaker 3m
29 Factorization Machines in SageMaker 4m
30 IP Insights in SageMaker 3m
31 Reinforcement Learning in SageMaker 12m
32 Automatic Model Tuning 6m
33 Apache Spark with SageMaker 3m
34 Amazon Comprehend 6m
35 Amazon Translate 2m
36 Amazon Transcribe 4m
37 Amazon Polly 6m
38 Amazon Rekognition 7m
39 Amazon Forecast 2m
40 Amazon Lex 3m
41 The Best of the Rest: Other High-Level AWS Machine Learning Services 3m
42 Putting them All Together 2m
43 Lab: Tuning a Convolutional Neural Network on EC2, Part 1 9m
44 Lab: Tuning a Convolutional Neural Network on EC2, Part 2 9m
45 Lab: Tuning a Convolutional Neural Network on EC2, Part 3 6m

01 Section Intro: Machine Learning Implementation and Operations 1m
02 SageMaker's Inner Details and Production Variants 11m
03 SageMaker On the Edge: SageMaker Neo and IoT Greengrass 4m
04 SageMaker Security: Encryption at Rest and In Transit 5m
05 SageMaker Security: VPC's, IAM, Logging, and Monitoring 4m
06 SageMaker Resource Management: Instance Types and Spot Training 4m
07 SageMaker Resource Management: Elastic Inference, Automatic Scaling, AZ's 5m
08 SageMaker Inference Pipelines 2m
09 Lab: Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 1 5m
10 Lab: Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 2 11m
11 Lab: Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 3 12m

01 Section Intro: Wrapping Up 1m
02 More Preparation Resources 6m
03 Test-Taking Strategies, and What to Expect 10m
04 You Made It! 1m
05 Save 50% on your AWS Exam Cost! 2m
06 Get an Extra 30 Minutes on your AWS Exam - Non Native English Speakers only 1m
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