Section 1 : INTRODUCTION, DATAML LINGO, AWS DATA STORAGE
Lecture 1 What makes this course unique 00:04:57 Duration
Lecture 2 AWS Machine Learning Exam Overview 00:09:06 Duration
Lecture 3 Course Outline 00:10:13 Duration
Lecture 4 BONUS Learning Path
Lecture 5 Guidelines and Best Practices 00:01:56 Duration
Lecture 6 Section Introduction
Lecture 7 What is Machine Learning and AI - Part 1 00:09:49 Duration
Lecture 8 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 9 Amazon Web Services 00:06:24 Duration
Lecture 10 AIML Data Lingo - Labeled vs 00:14:04 Duration
Lecture 11 AIML Data Lingo - Data Types 00:10:04 Duration
Lecture 12 Database vs
Lecture 13 AWS Storage S3 DynamoDB RDS 00:11:02 Duration
Lecture 14 GET YOUR BONUS MATERIALS
Lecture 15 Section 1 Slides

Section 2 : AMAZON S3
Lecture 1 Section Introduction 00:02:40 Duration
Lecture 2 Amazon S3 Partitions and Tags 00:13:44 Duration
Lecture 3 S3 Storage Tiers and LifeCycle Polices 00:07:48 Duration
Lecture 4 S3 Encryption 00:05:05 Duration
Lecture 5 S3 Security - Part 1 00:09:01 Duration
Lecture 6 S3 Security - Part 2 00:05:12 Duration
Lecture 7 Additional Information 00:03:23 Duration
Lecture 8 GET YOUR BONUS MATERIALS
Lecture 9 Section 2 Slides

Section 3 : AWS DATA MIGRATION, GLUE, PIPELINE, STEP and BATCH
Lecture 1 Section Introduction 00:03:18 Duration
Lecture 2 AWS Glue – part #1
Lecture 3 AWS Glue – part #2 00:08:40 Duration
Lecture 4 AWS Data Pipeline 00:07:34 Duration
Lecture 5 AWS Data Migration Service DMS 00:03:33 Duration
Lecture 6 AWS Batch 00:02:57 Duration
Lecture 7 AWS Step Function 00:08:31 Duration
Lecture 8 GET YOUR BONUS MATERIALS
Lecture 9 Section 3 Slides

Section 4 : DATA STREAMING AND KINESIS
Lecture 1 Section Introduction 00:05:06 Duration
Lecture 2 Kinesis Overview 00:07:57 Duration
Lecture 3 AWS Kinesis Video Streams - Part 1 00:05:43 Duration
Lecture 4 AWS Kinesis Video Streams - Part 2 00:07:43 Duration
Lecture 5 AWS Kinesis Data Streams - Part 1 00:05:21 Duration
Lecture 6 AWS Kinesis Data Streams - Part 2 00:06:57 Duration
Lecture 7 AWS Kinesis Firehose 00:06:05 Duration
Lecture 8 AWS Kinesis Analytics - Part 1 00:03:20 Duration
Lecture 9 AWS Kinesis Analytics - Part 2 00:07:54 Duration
Lecture 10 GET YOUR BONUS MATERIALS
Lecture 11 Section 4 Slides

Section 5 : JUPYTER NOTEBOOK, SCIKIT-LEARN, PYTHON PACKAGES, AND DISTRIBUTIONS
Lecture 1 Section Introduction 00:06:42 Duration
Lecture 2 Jupyter Notebooks and Scikit Learn 00:06:33 Duration
Lecture 3 Python Packages (Pandas, Numpy, Matplotlib and Seaborn)
Lecture 4 Data Visualization 00:07:09 Duration
Lecture 5 Distributions (Normal, Standard, Poisson, Bernoulli) 00:10:12 Duration
Lecture 6 Time Series 00:02:35 Duration
Lecture 7 GET YOUR BONUS MATERIALS
Lecture 8 Section 5 Slides

Section 6 : ATHENA, QUICKSIGHT, EMR
Lecture 1 Section Introduction 00:03:13 Duration
Lecture 2 Athena - Part 1 00:08:55 Duration
Lecture 3 Athena - Part 2 00:07:55 Duration
Lecture 4 Amazon Quicksight - Part 1 00:04:56 Duration
Lecture 5 Amazon Quicksight - Part 2 00:11:27 Duration
Lecture 6 Elastic Map Reduce - Part 1 00:10:03 Duration
Lecture 7 Elastic Map Reduce - Part 2 00:11:21 Duration
Lecture 8 EMR and Hadoop 00:07:20 Duration
Lecture 9 EMR and Spark 00:05:34 Duration
Lecture 10 GET YOUR BONUS MATERIALS
Lecture 11 Section 6 Slides

Section 7 : FEATURE ENGINEERING
Lecture 1 Introduction to Feature Engineering 00:02:31 Duration
Lecture 2 Feature Engineering Overview 00:08:37 Duration
Lecture 3 Amazon SageMaker GroundTruth 00:09:07 Duration
Lecture 4 Feature Selection 00:05:25 Duration
Lecture 5 Scaling 00:09:28 Duration
Lecture 6 Imputation 00:10:21 Duration
Lecture 7 Outliers 00:05:08 Duration
Lecture 8 One Hot Encoding 00:03:42 Duration
Lecture 9 Binning 00:05:27 Duration
Lecture 10 Log Transformation 00:03:32 Duration
Lecture 11 Shuffling, Feature Splitting, Unbalanced Datasets 00:06:25 Duration
Lecture 12 Text Feature Engineering overview 00:03:40 Duration
Lecture 13 Bag of words, punctuation, and dates (easy ones!) 00:04:47 Duration
Lecture 14 Term Frequency Inverse Document Frequency (TF-IDF) 00:06:44 Duration
Lecture 15 N-Grams (Unigram vs 00:05:37 Duration
Lecture 16 Orthogonal Sparse Bigram (OSB) 00:03:14 Duration
Lecture 17 Cartesian Product Transformation 00:03:36 Duration
Lecture 18 GET YOUR BONUS MATERIALS
Lecture 19 Section 7 Slides

Section 8 : MACHINE AND DEEP LEARNING BASICS - PART #1
Lecture 1 Section Introduction 00:08:53 Duration
Lecture 2 Artificial Neural Networks Basics Single Neuron Model 00:07:02 Duration
Lecture 3 Activation Functions 00:05:01 Duration
Lecture 4 Multi-Layer Perceptron Model 00:07:31 Duration
Lecture 5 How do Artificial Neural Networks Train 00:16:24 Duration
Lecture 6 ANN Parameters Tuning – Learning rate and batch size 00:10:49 Duration
Lecture 7 Tensorflow playground 00:14:40 Duration
Lecture 8 Gradient Descent and Backpropagation 00:09:03 Duration
Lecture 9 Overfitting and Under fitting 00:06:09 Duration
Lecture 10 How to overcome overfitting 00:09:28 Duration
Lecture 11 Bias Variance Trade-off 00:09:51 Duration
Lecture 12 L2 Regularization 00:07:48 Duration
Lecture 13 L1 Regularization 00:04:33 Duration
Lecture 14 GET YOUR BONUS MATERIALS
Lecture 15 Section 8 Slides

Section 9 : MACHINE AND DEEP LEARNING BASICS - PART #2
Lecture 1 Section Introduction 00:02:39 Duration
Lecture 2 Artificial Neural Networks Architectures
Lecture 3 Convolutional Neural Networks 00:18:54 Duration
Lecture 4 Recurrent Neural Networks 00:09:51 Duration
Lecture 5 Vanishing Gradient Problem 00:07:16 Duration
Lecture 6 Long Short Term Memory (LSTM) Networks 00:07:10 Duration
Lecture 7 Model Performance Assessment – Confusion Matrix 00:07:55 Duration
Lecture 8 Model Performance Assessment – Precision, recall, F1-score 00:16:43 Duration
Lecture 9 Model Performance Assessment – ROC, AUC, Heatmap, and RMSE 00:09:35 Duration
Lecture 10 Transfer Learning 00:11:36 Duration
Lecture 11 Ensemble Learning - Bagging and Boosting 00:09:57 Duration
Lecture 12 K Fold Cross Validation 00:02:15 Duration
Lecture 13 GET YOUR BONUS MATERIALS
Lecture 14 Section 9 Slides

Section 10 : MACHINE AND DEEP LEARNING IN AWS - PART #1
Lecture 1 Section Introduction 00:03:46 Duration
Lecture 2 AWS SageMaker 00:11:07 Duration
Lecture 3 AWS SageMaker Part 2 00:12:11 Duration
Lecture 4 Deep Learning on AWS 00:02:44 Duration
Lecture 5 SageMaker Built-in algorithms overview 00:06:36 Duration
Lecture 6 Object Detection 00:09:09 Duration
Lecture 7 Image classification 00:06:28 Duration
Lecture 8 Semantic Segmentation 00:08:07 Duration
Lecture 9 Linear Learner 00:06:58 Duration
Lecture 10 Factorization Machines 00:04:32 Duration
Lecture 11 XGboost 00:03:34 Duration
Lecture 12 Seq2Seq 00:05:55 Duration
Lecture 13 DeepAR 00:08:15 Duration
Lecture 14 Blazing Text 00:09:52 Duration
Lecture 15 GET YOUR BONUS MATERIALS
Lecture 16 Section 10 Slides

Section 11 : MACHINE AND DEEP LEARNING IN AWS - PART #2
Lecture 1 Section Introduction 00:03:11 Duration
Lecture 2 SageMaker Built-in Algorithms Overview 00:04:34 Duration
Lecture 3 Random Cut Forest 00:07:45 Duration
Lecture 4 K Nearest Neighbors KNN 00:09:09 Duration
Lecture 5 K Means 00:04:35 Duration
Lecture 6 Principal Component Analysis PCA 00:03:51 Duration
Lecture 7 IP Insights 00:05:43 Duration
Lecture 8 Reinforcement Learning 00:09:26 Duration
Lecture 9 Neural Topic Model NTM 00:03:24 Duration
Lecture 10 LDA 00:03:37 Duration
Lecture 11 Object2Vec 00:06:23 Duration
Lecture 12 Multi Model 00:01:55 Duration
Lecture 13 Automatic Model Tuning 00:08:40 Duration
Lecture 14 GET YOUR BONUS MATERIALS
Lecture 15 Section 11 Slides

Section 12 : AWS HIGH LEVEL AIML SERVICES
Lecture 1 Section Introduction 00:03:47 Duration
Lecture 2 SageMaker AIML High Level Services 00:02:42 Duration
Lecture 3 Top 5 AIML Services 00:15:05 Duration
Lecture 4 ReKognition 00:05:54 Duration
Lecture 5 Amazon Comprehend and Comprehend Medical 00:05:43 Duration
Lecture 6 Translate 00:05:46 Duration
Lecture 7 Transcribe 00:06:25 Duration
Lecture 8 Polly 00:02:04 Duration
Lecture 9 Forecast 00:05:45 Duration
Lecture 10 Lex 00:05:00 Duration
Lecture 11 Personalize 00:03:41 Duration
Lecture 12 Textract 00:02:31 Duration
Lecture 13 AWS DeepLens 00:04:12 Duration
Lecture 14 AWS DeepRacer 00:02:38 Duration
Lecture 15 GET YOUR BONUS MATERIALS
Lecture 16 Section 12 Slides

Section 13 : ML IMPLEMENTATION AND OPERATION
Lecture 1 Introduction 00:06:57 Duration
Lecture 2 SageMaker Components Review 00:08:15 Duration
Lecture 3 SageMaker Model Deployment 00:05:16 Duration
Lecture 4 Resources and Instance Types 00:13:04 Duration
Lecture 5 Online vs 00:09:09 Duration
Lecture 6 Production Variants and Canary Deployment 00:04:58 Duration
Lecture 7 SageMaker Neo 00:05:09 Duration
Lecture 8 AWS IoT Greengrass 00:03:40 Duration
Lecture 9 Docker Containers 00:07:28 Duration
Lecture 10 AWS Security Overview 00:05:53 Duration
Lecture 11 In-Transit and Rest Encryption 00:03:41 Duration
Lecture 12 AWS CloudWatch 00:04:15 Duration
Lecture 13 AWS CloudTrail 00:02:55 Duration
Lecture 14 Section 13 Slides