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AWS Machine Learning Certification Exam | Complete Guide

AWS Certified Machine Learning - Specialty

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AWS Machine Learning Certification Exam | Complete Guide

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Last updated 11/2021

Prof. Ryan Ahmed | 450K+ Students | Best-Selling Professor | 250K+ YouTube

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Lessons

Quizzes

Duration

13 Hours

Skill level

Beginner

Language

English

Certificate

Yes

Full lifetime access

Yes

Description

Update 01/02/2020: Section #13 on Machine Learning Implementation and Operations is released.
Machine and Deep Learning
are the hottest tech fields to master right now! Machine/Deep Learning techniques are widely adopted in many fields such as banking, healthcare, transportation and technology. Amazon has recently introduced the AWS machine Learning Certification Speciality exam and its quite challenging! AWS Certified Machine Learning Specialty is targeted at data scientists and developers who design, train and deploy AI/ML models to solve real-world challenging problems.
The bad news:
this exam is a very challenging AWS exam since it tests the candidate’s knowledge on multiple aspects such as (1) Data Engineering and Feature Engineering, (2) AI/ML Models selection, (3) Appropriate AWS services solution to solve business problem, (4) AI/ML models building, training, and deployment, (5) Model optimization and Hyperparameters tuning. You need to answer these questions in order to pass the exam:
o
How to select proper ML technique to solve a given business problem?
o
Which AWS service could work best for a given problem?
o
How to design, implement and scale secure ML solutions?
o
How to choose the most cost-effective solution?
The good news:
With over 500+ slides and over 50 practice questions, this course is by far the most comprehensive course on the market that provides students with the foundational knowledge to pass the AWS Machine Learning Certification exam like a pro! This course covers the most important concepts without any fillers or irrelevant information.
Who this course is for:
Developers and data scientists wanting to get certified in AWS Machine Learning

What you'll learn

Data Engineering

Data types, Python Libraries (pandas, Numpy, scikit Learn, MatplotLib, Seaborn), data distributions, timeseries, Feature Engineering (imputation, binning, encoding, and normalization)

AWS Services and Algorithms

Amazon SageMaker, Amazon S3 Storage services, AWS Glue

AWS Kinesis Services (Kinesis firehose, Kinesis video streams, Kinesis data streams, Kinesis analytics)

Redshift, Redshift Spectrum, DynamoDB, Athena, Amazon Quicksight, Elastic Map Reduce (EMR)

Rekognition, Lex, Polly, Comprehend, Translate, transcribe, BlazingText Word2Vec, DeepAR, Factorization Machines, Gradient Boosted Trees (XGBoost)

Image Classification (ResNet), IP Insights, K-Means Clustering, K-Nearest Neighbor (k-NN)

Latent Dirichlet Allocation (LDA), Linear Learner (Classification), Linear Learner (Regression)

Neural Topic Modelling (NTM), Object2Vec, Object Detection, Principal Component Analysis (PCA), Random Cut Forest, Semantic Segmentation, and Seqence2Sequence

Machine and Deep Learning Basics

Requirements

You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
No previous design experience is needed.
No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures

Expand All Sections

1-INTRODUCTION, DATA/ML LINGO, AWS DATA STORAGE

1.1-What makes this course unique?

1.2-AWS Machine Learning Exam Overview

1.3-Course Outline

1.4-EXTRA: Learning Path

1.5-Guidelines and Best Practices

1.6-Section Introduction

1.7-Section Introduction Quiz

1.8-What is Machine Learning and AI - Part 1

1.9-What is Machine Learning and AI - Part 1 Quiz

1.10-What is Machine Learning and AI - Part 2

1.11-What is Machine Learning and AI - Part 2 Quiz

1.12-Amazon Web Services

1.13-Amazon Web Services Quiz

1.14-AIML Data Lingo - Labeled vs. unlabeled

1.15-AIML Data Lingo - Labeled vs. unlabeled Quiz

1.16-AIML Data Lingo - Data Types

1.17-AIML Data Lingo - Data Types - quiz

1.18-Database vs. datalake vs. warehouse

1.19-Database vs. datalake vs. warehouse - Quiz

1.20-AWS Storage S3 DynamoDB RDS

1.21-AWS Storage S3 DynamoDB RDS Quiz

1.22-GET YOUR EXTRA MATERIALS

1.23-Section 1 Slides

2-AMAZON S3

2.1-Section Introduction

2.2-Amazon S3 Partitions and Tags

2.3-Amazon S3 Partitions and Tags Quiz

2.4-S3 Storage Tiers and LifeCycle Polices

2.5-S3 Storage Tiers and LifeCycle Polices Quiz

2.6-S3 Encryption

2.7-S3 Encryption Quiz

2.8-S3 Security - Part 1

2.9-S3 Security - Part 1 Quiz

2.10-S3 Security - Part 2

2.11-S3 Security - Part 2 Quiz

2.12-Additional Information

2.13-Additional Information Quiz

2.14-GET YOUR EXTRA MATERIALS

2.15-Section 2 Slides

3-AWS DATA MIGRATION, GLUE, PIPELINE, STEP and BATCH

3.1-Section Introduction

3.2-AWS Glue – part #1

3.3-AWS Glue – part #1 Quiz

3.4-AWS Glue – part #2

3.5-AWS Glue – part #2 Quiz

3.6-AWS Data Pipeline

3.7-AWS Data Pipeline Quiz

3.8-AWS Data Migration Service DMS

3.9-AWS Data Migration Service DMS Quiz

3.10-AWS Batch

3.11-AWS Batch Quiz

3.12-AWS Step Function

3.13-AWS Step Function Quiz

3.14-GET YOUR EXTRA MATERIALS

3.15-Section 3 Slides

4-DATA STREAMING AND KINESIS

4.1-Section Introduction

4.2-Section Introduction Quiz

4.3-Kinesis Overview

4.4-Kinesis Overview Quiz

4.5-AWS Kinesis Video Streams - Part 1

4.6-AWS Kinesis Video Streams - Part 1 Quiz

4.7-AWS Kinesis Video Streams - Part 2

4.8-AWS Kinesis Video Streams - Part 2 Quiz

4.9-AWS Kinesis Data Streams - Part 1

4.10-AWS Kinesis Data Streams - Part 1 Quiz

4.11-AWS Kinesis Data Streams - Part 2

4.12-AWS Kinesis Data Streams - Part 2 - Quiz

4.13-AWS Kinesis Firehose

4.14-AWS Kinesis Firehose - Quiz

4.15-AWS Kinesis Analytics - Part 1

4.16-AWS Kinesis Analytics - Part 1 - Quiz

4.17-AWS Kinesis Analytics - Part 2

4.18-AWS Kinesis Analytics - Part 2 - Quiz

4.19-GET YOUR EXTRA MATERIALS

4.20-Section 4 Slides

5-JUPYTER NOTEBOOK, SCIKIT-LEARN, PYTHON PACKAGES, AND DISTRIBUTIONS

5.1-Section Introduction

5.2-Jupyter Notebooks and Scikit Learn

5.3-Jupyter Notebooks and Scikit Learn Quiz

5.4-Python Packages (Pandas, Numpy, Matplotlib and Seaborn)

5.5-Python Packages (Pandas, Numpy, Matplotlib and Seaborn) Quiz

5.6-Data Visualization

5.7-Data Visualization - Quiz

5.8-Distributions (Normal, Standard, Poisson, Bernoulli)

5.9-Distributions (Normal, Standard, Poisson, Bernoulli) - Quiz

5.10-Time Series

5.11-Time Series - Quiz

5.12-GET YOUR EXTRA MATERIALS

5.13-Section 5 Slides

6-ATHENA, QUICKSIGHT, EMR

6.1-Section Introduction

6.2-Athena - Part 1

6.3-Athena - Part 1 - Quiz

6.4-Athena - Part 2

6.5-Athena - Part 2 - Quiz

6.6-Amazon Quicksight - Part 1

6.7-Amazon Quicksight - Part 1 - Quiz

6.8-Amazon Quicksight - Part 2

6.9-Amazon Quicksight - Part 2 - Quiz

6.10-Elastic Map Reduce - Part 1

6.11-Elastic Map Reduce - Part 1 - Quiz

6.12-Elastic Map Reduce - Part 2

6.13-Elastic Map Reduce - Part 2 - Quiz

6.14-EMR and Hadoop

6.15-EMR and Hadoop - Quiz

6.16-EMR and Spark

6.17-EMR and Spark - Quiz

6.18-GET YOUR EXTRA MATERIALS

6.19-Section 6 Slides

7-FEATURE ENGINEERING

7.1-Introduction to Feature Engineering

7.2-Feature Engineering Overview

7.3-Feature Engineering Overview - Quiz

7.4-Amazon SageMaker GroundTruth

7.5-Amazon SageMaker GroundTruth - Quiz

7.6-Feature Selection

7.7-Feature Selection - Quiz

7.8-Scaling

7.9-Saling Quiz

7.10-Imputation

7.11-Imputation - Quiz

7.12-Outliers

7.13-Outliers - Quiz

7.14-One Hot Encoding

7.15-One Hot Encoding - Quiz

7.16-Binning

7.17-Binning - Quiz

7.18-Log Transformation

7.19-Log Transformation - Quiz

7.20-Shuffling, Feature Splitting, Unbalanced Datasets

7.21-Shuffling, Feature Splitting, Unbalanced Datasets Quiz

7.22-Text Feature Engineering overview

7.23-Text Feature Engineering overview - Quiz

7.24-Bag of words, punctuation, and dates (easy ones!)

7.25-Bag of words, punctuation, and dates (easy ones!) - Quiz

7.26-Term Frequency Inverse Document Frequency (TF-IDF)

7.27-Term Frequency Inverse Document Frequency (TF-IDF) - Quiz

7.28-N-Grams (Unigram vs. Bigram vs. Trigram)

7.29-N-Grams (Unigram vs. Bigram vs. Trigram) - Quiz

7.30-Orthogonal Sparse Bigram (OSB)

7.31-Orthogonal Sparse Bigram (OSB) - Quiz

7.32-Cartesian Product Transformation

7.33-Cartesian Product Transformation - Quiz

7.34-GET YOUR EXTRA MATERIALS

7.35-Section 7 Slides

8-MACHINE AND DEEP LEARNING BASICS - PART #1

8.1-Section Introduction

8.2-Artificial Neural Networks Basics: Single Neuron Model

8.3-Artificial Neural Networks Basics: Single Neuron Model - Quiz

8.4-Activation Functions

8.5-Activation Function - Quiz

8.6-Multi-Layer Perceptron Model

8.7-Multi-Layer Perceptron Model - Quiz

8.8-How do Artificial Neural Networks Train?

8.9-How do Artificial Neural Networks Train? - Quiz

8.10-ANN Parameters Tuning – Learning rate and batch size

8.11-ANN Parameters Tuning – Learning rate and batch size - Quiz

8.12-Tensorflow playground

8.13-Gradient Descent and Backpropagation

8.14-Gradient Descent and Backpropagation - Quiz

8.15-Overfitting and Under fitting

8.16-Overfitting and Under fitting - Quiz

8.17-How to overcome overfitting?

8.18-How to overcome overfitting? - Quiz

8.19-Bias Variance Trade-off

8.20-Bias Variance Trade-off - Quiz

8.21-L2 Regularization

8.22-L2 Regularization - Quiz

8.23-L1 Regularization

8.24-L1 Regularization - Quiz

8.25-GET YOUR EXTRA MATERIALS

8.26-Section 8 Slides

9-MACHINE AND DEEP LEARNING BASICS - PART #2

9.1-Section Introduction

9.2-Artificial Neural Networks Architectures

9.3-Artificial Neural Networks Architectures - Quiz

9.4-Convolutional Neural Networks

9.5-Convolutional Neural Networks - Quiz

9.6-Recurrent Neural Networks

9.7-Recurrent Neural Networks - Quiz

9.8-Vanishing Gradient Problem

9.9-Vanishing Gradient Problem - Quiz

9.10-Long Short Term Memory (LSTM) Networks

9.11-Long Short Term Memory (LSTM) Networks - Quiz

9.12-Model Performance Assessment – Confusion Matrix

9.13-Model Performance Assessment – Confusion Matrix - Quiz

9.14-Model Performance Assessment – Precision, recall, F1-score

9.15-Model Performance Assessment – Precision, recall, F1-score - Quiz

9.16-Model Performance Assessment – ROC, AUC, Heatmap, and RMSE

9.17-Model Performance Assessment – ROC, AUC, Heatmap, and RMSE - Quiz

9.18-Transfer Learning

9.19-Transfer Learning - Quiz

9.20-Ensemble Learning - Bagging and Boosting

9.21-Ensemble Learning - Bagging and Boosting - Quiz

9.22-K Fold Cross Validation

9.23-K Fold Cross Validation - Quiz

9.24-GET YOUR EXTRA MATERIALS

9.25-Section 9 Slides

10-MACHINE AND DEEP LEARNING IN AWS - PART #1

10.1-Section Introduction

10.2-AWS SageMaker

10.3-AWS Sagemaker - Quiz

10.4-AWS SageMaker Part 2

10.5-AWS Sagemaker Part 2 - Quiz

10.6-Deep Learning on AWS

10.7-Deep Learning on AWS - Quiz

10.8-SageMaker Built-in algorithms overview

10.9-SageMaker Built-in algorithms overview - Quiz

10.10-Object Detection

10.11-Object Detection - Quiz

10.12-Image classification

10.13-Image classification - Quiz

10.14-Semantic Segmentation

10.15-Semantic Segmentation - QUiz

10.16-Linear Learner

10.17-Linear Learner - Quiz

10.18-Factorization Machines

10.19-Factorization Machines - Quiz

10.20-XGboost

10.21-XGboost - Quiz

10.22-Seq2Seq

10.23-Seq2Seq - Quiz

10.24-DeepAR

10.25-DeepAR - Quiz

10.26-Blazing Text

10.27-Blazing Text - Quiz

10.28-GET YOUR EXTRA MATERIALS

10.29-Section 10 Slides

11-MACHINE AND DEEP LEARNING IN AWS - PART #2

11.1-Section Introduction

11.2-SageMaker Built-in Algorithms Overview

11.3-Random Cut Forest

11.4-Random Cut Forest - Quiz

11.5-K Nearest Neighbors KNN

11.6-K Nearest Neighbors KNN - Quiz

11.7-K Means

11.8-K-Means Quiz

11.9-Principal Component Analysis PCA

11.10-Principal Component Analysis PCA - Quiz

11.11-IP Insights

11.12-IP Insights - Quiz

11.13-Reinforcement Learning

11.14-Reinforcement Learning - Quiz

11.15-Neural Topic Model NTM

11.16-Neural Topic Model NTM - Quiz

11.17-LDA

11.18-LDA - Quiz

11.19-Object2Vec

11.20-Object2Vec - Quiz

11.21-Multi Model

11.22-Multi Model - Quiz

11.23-Automatic Model Tuning

11.24-Automatic Model Tuning - Quiz

11.25-GET YOUR EXTRA MATERIALS

11.26-Section 11 Slides

12-AWS HIGH LEVEL AI/ML SERVICES

12.1-Section Introduction

12.2-SageMaker AIML High Level Services

12.3-Top 5 AI/ML Services

12.4-ReKognition

12.5-ReKognition - Quiz

12.6-Amazon Comprehend and Comprehend Medical

12.7-Amazon Comprehend and Comprehend Medical - Quiz

12.8-Translate

12.9-Translate - Quiz

12.10-Transcribe

12.11-Transcribe - Quiz

12.12-Polly

12.13-Polly - Quiz

12.14-Forecast

12.15-Forecast - Quiz

12.16-Lex

12.17-Lex - Quiz

12.18-Personalize

12.19-Personalize - Quiz

12.20-Textract

12.21-Textract - Quiz

12.22-AWS DeepLens

12.23-AWS DeepLens - Quiz

12.24-AWS DeepRacer

12.25-AWS DeepRacer - Quiz

12.26-GET YOUR EXTRA MATERIALS

12.27-Section 12 Slides

13-ML IMPLEMENTATION AND OPERATION

13.1-Introduction

13.2-SageMaker Components Review

13.3-SageMaker Components Review - Quiz

13.4-SageMaker Model Deployment

13.5-SageMaker Model Deployment - Quiz

13.6-Resources and Instance Types

13.7-Resources and Instance Types - Quiz

13.8-Online vs. Offline Validation

13.9-Online vs. Offline Validation - Quiz

13.10-Production Variants and Canary Deployment

13.11-Production Variants and Canary Deployment - Quiz

13.12-SageMaker Neo

13.13-SageMaker Neo - Quiz

13.14-AWS IoT Greengrass

13.15-AWS IoT Greengrass - Quiz

13.16-Docker Containers

13.17-Docker Containers - Quiz

13.18-AWS Security Overview

13.19-AWS Security Overview - Quiz

13.20-In-Transit and Rest Encryption

13.21-In-Transit and Rest Encryption - Quiz

13.22-AWS CloudWatch

13.23-AWS CloudWatch - Quiz

13.24-AWS CloudTrail

13.25-AWS CloudTrail - Quiz

13.26-Section 13 Slides

14-Congratulations!! Don't forget your Prize :)

14.1-Bonus: How To UNLOCK Top Salaries (Live Training)

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AWS Machine Learning Certification Exam | Complete Guide

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