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

Name: AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01)
Rating: 4.4 (743 reviews)

Get ready for your exam by enrolling in our comprehensive training course. This course includes a full set of instructional videos designed to equip you with in-depth knowledge essential for passing the certification exam with flying colors.

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Introduction

1. Course Introduction: What to Expect
6m

Data Engineering

1. Section Intro: Data Engineering
1m
2. Amazon S3 - Overview
5m
3. Amazon S3 - Storage Tiers & Lifecycle Rules
4m
4. Amazon S3 Security
8m
5. Kinesis Data Streams & Kinesis Data Firehose
9m
6. Lab 1.1 - Kinesis Data Firehose
6m
7. Kinesis Data Analytics
4m
8. Lab 1.2 - Kinesis Data Analytics
7m
9. 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

Exploratory Data Analysis

1. Section Intro: Data Analysis
1m
2. Python in Data Science and Machine Learning
12m
3. Example: Preparing Data for Machine Learning in a Jupyter Notebook.
10m
4. Types of Data
5m
5. Data Distributions
6m
6. Time Series: Trends and Seasonality
4m
7. Introduction to Amazon Athena
5m
8. Overview of Amazon Quicksight
6m
9. 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

Modeling

1. Section Intro: Modeling
2m
2. Introduction to Deep Learning
9m
3. Convolutional Neural Networks
12m
4. Recurrent Neural Networks
11m
5. Deep Learning on EC2 and EMR
2m
6. Tuning Neural Networks
5m
7. Regularization Techniques for Neural Networks (Dropout, Early Stopping)
7m
8. Grief with Gradients: The Vanishing Gradient problem
4m
9. 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

ML Implementation and Operations

1. Section Intro: Machine Learning Implementation and Operations
1m
2. SageMaker's Inner Details and Production Variants
11m
3. SageMaker On the Edge: SageMaker Neo and IoT Greengrass
4m
4. SageMaker Security: Encryption at Rest and In Transit
5m
5. SageMaker Security: VPC's, IAM, Logging, and Monitoring
4m
6. SageMaker Resource Management: Instance Types and Spot Training
4m
7. SageMaker Resource Management: Elastic Inference, Automatic Scaling, AZ's
5m
8. SageMaker Inference Pipelines
2m
9. 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

Wrapping Up

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