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MLS-C01 - AWS Certified Machine Learning Specialty

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MLS-C01 - AWS Certified Machine Learning Specialty

  • Students: 402
  • Lectures: 106
  • Duration: 09h

About This Course


Passing the MLS-C01 exam could be a real challenge, and when you don’t have time to prepare for the exam, you need quality study guides, tutorials and practice exam questions. Created by certified Amazon Specialists, the 106 Online Course Tutorial for the MLS-C01 - AWS Certified Machine Learning Specialty exam is a must. The MLS-C01 Video Tutorial is a great addition to your studies which are a plus, due to the visual and audio aid in the MLS-C01 Online Course Tutorial.

The MLS-C01 - AWS Certified Machine Learning Specialty covers all the exam objectives you will be tested on for the MLS-C01 exam. The MLS-C01 Online Course offers a complete curriculum with in-depth knowledge, labs and relevant examples to better prepare yourself for the Amazon MLS-C01 exam. The MLS-C01 - AWS Certified Machine Learning Specialty Online Course is ready to use as soon as you complete the purchase and can be played from your Members Area. Excellent Add-On to the MLS-C01 practice exam to better prepare you for the MLS-C01 exam.

Curriculum For This Course

1. Course Introduction: What to Expect 00:06:09

1. Section Intro: Data Engineering 00:01:04
2. Amazon S3 - Overview 00:05:04
3. Amazon S3 - Storage Tiers and Lifecycle Rules 00:04:29
4. Amazon S3 Security 00:08:05
5. Kinesis Data Streams and Kinesis Data Firehose 00:08:38
6. Lab 1.1 - Kinesis Data Firehose 00:06:04
7. Kinesis Data Analytics 00:04:25
8. Lab 1.2 - Kinesis Data Analytics 00:07:23
9. Kinesis Video Streams 00:02:55
10. Kinesis ML Summary 00:01:12
11. Glue Data Catalog and Crawlers 00:02:32
12. Lab 1.3 - Glue Data Catalog 00:04:23
13. Glue ETL 00:02:10
14. Lab 1.4 - Glue ETL 00:06:20
15. Lab 1.5 - Athena 00:01:26
16. Lab 1 - Cleanup 00:01:32
17. AWS Data Stores in Machine Learning 00:03:09
18. AWS Data Pipelines 00:02:39
19. AWS Batch 00:01:51
20. AWS DMS - Database Migration Services 00:01:58
21. AWS Step Functions 00:02:44
22. Full Data Engineering Pipelines 00:05:09

1. Section Intro - Data Analysis 00:01:12
2. Python in Data Science and Machine Learning 00:12:08
3. Example - Preparing Data for Machine Learning in a Jupyter Notebook 00:10:21
4. Types of Data 00:04:31
5. Data Distributions 00:06:05
6. Time Series - Trends and Seasonality 00:03:57
7. Introduction to Amazon Athena 00:05:06
8. Overview of Amazon Quicksight 00:05:59
9. Types of Visualizations, and When to Use Them 00:04:46
10. Elastic MapReduce (EMR) and Hadoop Overview 00:07:14
11. Apache Spark on EMR 00:09:59
12. EMR Notebooks, Security, and Instance Types 00:04:10
13. Feature Engineering and the Curse of Dimensionality 00:06:34
14. Imputing Missing Data 00:08:04
15. Dealing with Unbalanced Data 00:05:35
16. Handling Outliers 00:08:30
17. Binning, Transforming, Encoding, Scaling, and Shuffling 00:07:59
18. Amazon SageMaker Ground Truth and Label Generation 00:04:28
19. Lab: Preparing Data for TF-IDF with Spark and EMR, Part 1 00:06:18
20. Lab: Preparing Data for TF-IDF with Spark and EMR, Part 2 00:09:46
21. Lab: Preparing Data for TF-IDF with Spark and EMR, Part 3 00:13:31

1. Section Intro - Modeling 00:01:47
2. Introduction to Deep Learning 00:09:23
3. Convolutional Neural Networks 00:12:09
4. Recurrent Neural Networks 00:10:48
5. Deep Learning on EC2 and EMR 00:01:32
6. Tuning Neural Networks 00:04:48
7. Regularization Techniques for Neural Networks 00:06:41
8. Grief with Gradients: The Vanishing Gradient problem 00:04:28
9. L1 and L2 Regularization 00:03:04
10. The Confusion Matrix 00:05:30
11. Precision, Recall, F1, AUC, and more 00:07:04
12. Ensemble Methods: Bagging and Boosting 00:03:43
13. Introducing Amazon SageMaker 00:08:06
14. Linear Learner in SageMaker 00:04:59
15. XGBoost in SageMaker 00:02:55
16. Seq2Seq in SageMaker 00:04:47
17. DeepAR in SageMaker 00:04:06
18. BlazingText in SageMaker 00:04:55
19. Object2Vec in SageMaker 00:04:44
20. Object Detection in SageMaker 00:04:02
21. Image Classification in SageMaker 00:04:08
22. Semantic Segmentation in SageMaker 00:03:48
23. Random Cut Forest in SageMaker 00:03:01
24. Neural Topic Model in SageMaker 00:03:25
25. Latent Dirichlet Allocation (LDA) in SageMaker 00:03:09
26. K-Nearest-Neighbors (KNN) in SageMaker 00:02:59
27. K-Means Clustering in SageMaker 00:05:00
28. Principal Component Analysis (PCA) in SageMaker 00:03:20
29. Factorization Machines in SageMaker 00:04:11
30. IP Insights in SageMaker 00:02:58
31. Reinforcement Learning in SageMaker 00:12:23
32. Automatic Model Tuning 00:05:55
33. Apache Spark with SageMaker 00:03:17
34. Amazon Comprehend 00:05:49
35. Amazon Translate 00:01:54
36. Amazon Transcribe 00:04:16
37. Amazon Polly 00:05:38
38. Amazon Rekognition 00:06:39
39. Amazon Forecast 00:01:45
40. Amazon Lex 00:03:07
41. The Best of the Rest - Other High-Level AWS Machine Learning Services 00:02:50
42. Putting them All Together 00:02:08
43. Lab - Tuning a Convolutional Neural Network on EC2, Part 1 00:08:59
44. Lab - Tuning a Convolutional Neural Network on EC2, Part 2 00:09:06
45. Lab - Tuning a Convolutional Neural Network on EC2, Part 3 00:06:29

1. Section Intro - Machine Learning Implementation and Operations 00:01:10
2. SageMaker's Inner Details and Production Variants 00:11:09
3. SageMaker On the Edge: SageMaker Neo and IoT Greengrass 00:04:18
4. SageMaker Security: Encryption at Rest and In Transit 00:04:31
5. SageMaker Security - VPC's, IAM, Logging, and Monitoring 00:04:02
6. SageMaker Resource Management - Instance Types and Spot Training 00:03:35
7. SageMaker Resource Management - Elastic Inference, Automatic Scaling, AZ's 00:04:34
8. SageMaker Inference Pipelines 00:01:39
9. Lab: Tuning - Deploying, and Predicting with Tensorflow on SageMaker - Part 1 00:05:20
10. Lab - Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 3 00:12:20
10. Lab - Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 2 00:10:33

1. Section Intro: Wrapping Up 00:00:24
2. More Preparation Resources 00:05:52
3. Test-Taking Strategies, and What to Expect 00:10:04
4. You Made It! 00:00:46
5. Save 50% on your AWS Exam Cost! 00:01:42
6. Get an Extra 30 Minutes on your AWS Exam - Non Native English Speakers only 00:01:09