
AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01) Certification Video Training Course
The complete solution to prepare for for your exam with AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01) certification video training course. The AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01) certification video training course contains a complete set of videos that will provide you with thorough knowledge to understand the key concepts. Top notch prep including Amazon AWS Certified Machine Learning - Specialty exam dumps, study guide & practice test questions and answers.
AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01) Certification Video Training Course Exam Curriculum
Introduction
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1. Course Introduction: What to Expect
Data Engineering
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1. Section Intro: Data Engineering
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2. Amazon S3 - Overview
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3. Amazon S3 - Storage Tiers & Lifecycle Rules
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4. Amazon S3 Security
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5. Kinesis Data Streams & Kinesis Data Firehose
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6. Lab 1.1 - Kinesis Data Firehose
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7. Kinesis Data Analytics
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8. Lab 1.2 - Kinesis Data Analytics
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9. Kinesis Video Streams
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10. Kinesis ML Summary
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11. Glue Data Catalog & Crawlers
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12. Lab 1.3 - Glue Data Catalog
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13. Glue ETL
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14. Lab 1.4 - Glue ETL
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15. Lab 1.5 - Athena
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16. Lab 1 - Cleanup
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17. AWS Data Stores in Machine Learning
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18. AWS Data Pipelines
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19. AWS Batch
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20. AWS DMS - Database Migration Services
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21. AWS Step Functions
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22. Full Data Engineering Pipelines
Exploratory Data Analysis
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1. Section Intro: Data Analysis
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2. Python in Data Science and Machine Learning
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3. Example: Preparing Data for Machine Learning in a Jupyter Notebook.
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4. Types of Data
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5. Data Distributions
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6. Time Series: Trends and Seasonality
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7. Introduction to Amazon Athena
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8. Overview of Amazon Quicksight
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9. Types of Visualizations, and When to Use Them.
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10. Elastic MapReduce (EMR) and Hadoop Overview
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11. Apache Spark on EMR
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12. EMR Notebooks, Security, and Instance Types
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13. Feature Engineering and the Curse of Dimensionality
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14. Imputing Missing Data
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15. Dealing with Unbalanced Data
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16. Handling Outliers
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17. Binning, Transforming, Encoding, Scaling, and Shuffling
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18. Amazon SageMaker Ground Truth and Label Generation
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19. Lab: Preparing Data for TF-IDF with Spark and EMR, Part 1
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20. Lab: Preparing Data for TF-IDF with Spark and EMR, Part 2
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21. Lab: Preparing Data for TF-IDF with Spark and EMR, Part 3
Modeling
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1. Section Intro: Modeling
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2. Introduction to Deep Learning
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3. Convolutional Neural Networks
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4. Recurrent Neural Networks
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5. Deep Learning on EC2 and EMR
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6. Tuning Neural Networks
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7. Regularization Techniques for Neural Networks (Dropout, Early Stopping)
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8. Grief with Gradients: The Vanishing Gradient problem
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9. L1 and L2 Regularization
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10. The Confusion Matrix
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11. Precision, Recall, F1, AUC, and more
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12. Ensemble Methods: Bagging and Boosting
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13. Introducing Amazon SageMaker
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14. Linear Learner in SageMaker
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15. XGBoost in SageMaker
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16. Seq2Seq in SageMaker
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17. DeepAR in SageMaker
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18. BlazingText in SageMaker
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19. Object2Vec in SageMaker
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20. Object Detection in SageMaker
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21. Image Classification in SageMaker
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22. Semantic Segmentation in SageMaker
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23. Random Cut Forest in SageMaker
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24. Neural Topic Model in SageMaker
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25. Latent Dirichlet Allocation (LDA) in SageMaker
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26. K-Nearest-Neighbors (KNN) in SageMaker
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27. K-Means Clustering in SageMaker
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28. Principal Component Analysis (PCA) in SageMaker
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29. Factorization Machines in SageMaker
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30. IP Insights in SageMaker
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31. Reinforcement Learning in SageMaker
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32. Automatic Model Tuning
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33. Apache Spark with SageMaker
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34. Amazon Comprehend
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35. Amazon Translate
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36. Amazon Transcribe
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37. Amazon Polly
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38. Amazon Rekognition
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39. Amazon Forecast
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40. Amazon Lex
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41. The Best of the Rest: Other High-Level AWS Machine Learning Services
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42. Putting them All Together
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43. Lab: Tuning a Convolutional Neural Network on EC2, Part 1
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44. Lab: Tuning a Convolutional Neural Network on EC2, Part 2
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45. Lab: Tuning a Convolutional Neural Network on EC2, Part 3
ML Implementation and Operations
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1. Section Intro: Machine Learning Implementation and Operations
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2. SageMaker's Inner Details and Production Variants
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3. SageMaker On the Edge: SageMaker Neo and IoT Greengrass
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4. SageMaker Security: Encryption at Rest and In Transit
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5. SageMaker Security: VPC's, IAM, Logging, and Monitoring
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6. SageMaker Resource Management: Instance Types and Spot Training
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7. SageMaker Resource Management: Elastic Inference, Automatic Scaling, AZ's
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8. SageMaker Inference Pipelines
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9. Lab: Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 1
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10. Lab: Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 2
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11. Lab: Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 3
Wrapping Up
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1. Section Intro: Wrapping Up
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2. More Preparation Resources
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3. Test-Taking Strategies, and What to Expect
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4. You Made It!
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5. Save 50% on your AWS Exam Cost!
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6. Get an Extra 30 Minutes on your AWS Exam - Non Native English Speakers only
About AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01) Certification Video Training Course
AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01) certification video training course by prepaway along with practice test questions and answers, study guide and exam dumps provides the ultimate training package to help you pass.
Prepaway's AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01) video training course for passing certification exams is the only solution which you need.
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AWS Certified Machine Learning - Specialty Premium Bundle
- Premium File 369 Questions & Answers. Last update: Jun 09, 2025
- Training Course 106 Video Lectures
- Study Guide 275 Pages
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