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AWS Certified Big Data Specialty 2019 – In Depth & Hands On!

Comprehensive, hands-on AWS Big Data certification prep, with a practice exam! Kinesis, EMR, DynamoDB, Redshift and more
Instructor:
Sundog Education by Frank Kane
3,864 students enrolled
English [Auto-generated]
Maximize your odds of passing the AWS Certified Big Data exam
Move and transform massive data streams with Kinesis
Store big data with S3 and DynamoDB in a scalable, secure manner
Process big data with AWS Lambda and Glue ETL
Use the Hadoop ecosystem with AWS using Elastic MapReduce
Apply machine learning to massive data sets with Amazon ML, SageMaker, and deep learning
Analyze big data with Kinesis Analytics, Amazon Elasticsearch Service, Redshift, RDS, and Aurora
Visualize big data in the cloud using AWS QuickSight

The AWS Certified Big Data Specialty Exam is one of the most challenging certification exams you can take from Amazon. Passing it tells employers in no uncertain terms that your knowledge of big data systems is wide and deep. But, even experienced technologists need to prepare heavily for this exam. This course sets you up for success, by covering all of the big data technologies on the exam and how they fit together.

Best-selling Udemy instructors Frank Kane and Stéphane Maarek have teamed up to deliver the most comprehensive and hands-on prep course we’ve seen. Together, they’ve taught over 300,000 people around the world. This course combines Stéphane’s depth on AWS with Frank’s experience in Big Data, gleaned during his 9-year career at Amazon itself. Both Frank and Stéphane have taken and passed the exam themselves on the first try.

The world of big data on AWS includes a dizzying array of technologies and services. Just a sampling of the topics we cover in-depth are:

  • Streaming massive data with AWS Kinesis

  • Queuing messages with Simple Queue Service (SQS)

  • Wrangling the explosion data from the Internet of Things (IOT)

  • Transitioning from small to big data with the AWS Database Migration Service (DMS)

  • Storing massive data lakes with the Simple Storage Service (S3)

  • Optimizing transactional queries with DynamoDB

  • Tying your big data systems together with AWS Lambda

  • Making unstructured data query-able with AWS Glue

  • Processing data at unlimited scale with Elastic MapReduce, including Apache Spark, Hive, HBase, Presto, Zeppelin, Splunk, and Flume

  • Predicting values and classifications with the Amazon Machine Learning Service

  • Applying neural networks at massive scale with Deep Learning, MXNet, and Tensorflow

  • Applying advanced machine learning algorithms at scale with Amazon SageMaker

  • Analyzing streaming data in real-time with Kinesis Analytics

  • Searching and analyzing petabyte-scale data with Amazon Elasticsearch Service

  • Querying S3 data lakes with Amazon Athena

  • Hosting massive-scale data warehouses with Redshift and Redshift Spectrum

  • Integrating smaller data with your big data, using the Relational Database Service (RDS) and Aurora

  • Visualizing your data interactively with Quicksight

  • Keeping your data secure with encryption, KMS, HSM, IAM, Cognito, STS, and more

Throughout the course, you’ll have lots of opportunities to reinforce your learning with hands-on exercises and quizzes. And when you’re done, this course includes a practice exam that’s very similar to the real exam in difficulty, length, and style – so you’ll know if you’re ready before you invest in taking it. We’ll also arm you with some valuable test-taking tips and strategies along the way.

Big Data is an advanced certification, and it’s best tackled by students who have already obtained associate-level certification in AWS and have some real-world industry experience. This exam is not intended for AWS beginners.

You want to go into the AWS Certified Big Data Specialty Exam with confidence, and that’s what this course delivers. Hit the enroll button, and we’re excited to see you in the course… and ultimately to see you get your certification!

Introduction

1
Course Overview
2
Introducing our Hands-On Case Study: Cadabra.com
3
Udemy 101

If you're new to Udemy, learn how to have the best experience with the Q&A feature, video controls, transcripts, captions, and reviews.

4
Get the Course Materials
5
Cost of the Course + AWS Budget Setup

Domain 1: Collection

1
Collection Section Introduction
2
Kinesis Data Streams Overview
3
Kinesis Producers
4
Kinesis Consumers
5
Kinesis Enhanced Fan Out
6
Kinesis Scaling
7
Kinesis Security
8
Kinesis Data Firehose
9
[Exercise] Kinesis Firehose, Part 1

We'll build up a system to populate an S3 data lake from EC2 server data, using Kinesis Firehose.

10
[Exercise] Kinesis Firehose, Part 2

We'll build up a system to populate an S3 data lake from EC2 server data, using Kinesis Firehose.

11
[Exercise] Kinesis Firehose, Part 3

We'll build up a system to populate an S3 data lake from EC2 server data, using Kinesis Firehose.

12
Troubleshooting tips for the following exercise
13
[Exercise] Kinesis Data Streams

We'll create a Kinesis stream, and use the Kinesis Agent to send data from EC2 into it - and confirm data is being successfully sent and received. This will form the basis of our "order history app" that we'll build up across future exercises in this course.

14
SQS Overview
15
Kinesis Data Streams vs SQS
16
IoT Overview
17
IoT Components Deep Dive
18
Database Migration Service (DMS)
19
Direct Connect
20
Snowball
21
Collection Quiz

Domain 2: Storage

1
S3 Overview
2
S3 Storage Tiers
3
S3 Lifecycle Rules
4
S3 Versioning
5
S3 Cross Region Replication
6
S3 ETags
7
S3 Performance
8
S3 Encryption
9
S3 Security
10
Glacier & Vault Lock Policies
11
DynamoDB Overview
12
DynamoDB RCU & WCU
13
DynamoDB Partitions
14
DynamoDB APIs
15
DynamoDB Indexes: LSI & GSI
16
DynamoDB DAX
17
DynamoDB Streams
18
DynamoDB TTL
19
DynamoDB Security
20
[Exercise] DynamoDB

We'll continue to flesh out our "order history app" by writing our order data from a Kinesis stream into a DynamoDB table, using a Kinesis consumer app on EC2 for now to bridge the two.

21
ElastiCache Overview
22
Storage Quiz

Domain 3: Processing

1
Section Introduction: Processing
2
What is AWS Lambda?
3
Lambda Integration - Part 1
4
Lambda Integration - Part 2
5
Lambda Costs, Promises, and Anti-Patterns
6
[Exercise] AWS Lambda

We'll complete our "order history app" example by replacing our Kinesis consumer app with a Lambda function, which is serverless and more scalable.

7
Quiz: AWS Lambda

Check the depth of your knowledge on AWS Lambda - you'll need to have listened carefully to the previous lectures!

8
What is Glue? + Partitioning your Data Lake
9
Glue, Hive, and ETL
10
Glue Costs and Anti-Patterns
11
Quiz: AWS Glue

Check your knowledge on some of the finer points of AWS Glue crawlers, data catalogs, and ETL jobs.

12
Elastic MapReduce (EMR) Architecture and Usage
13
EMR, AWS integration, and Storage
14
EMR Promises; Intro to Hadoop
15
Intro to Apache Spark
16
Spark Integration with Kinesis and Redshift
17
Hive on EMR
18
Pig on EMR
19
HBase on EMR
20
Presto on EMR
21
Zeppelin and EMR Notebooks
22
Hue, Splunk, and Flume
23
S3DistCP and Other Services
24
EMR Security and Instance Types
25
[Exercise] Elastic MapReduce, Part 1

Let's use Apache Spark and it's machine learning library, MLLib, on an Amazon EMR cluster - to consume our order data in an S3 data lake, and produce product recommendations for our customers.

26
[Exercise] Elastic MapReduce, Part 2

Let's use Apache Spark and it's machine learning library, MLLib, on an Amazon EMR cluster - to consume our order data in an S3 data lake, and produce product recommendations for our customers.

27
[Quiz] EMR and the Hadoop Ecosystem

The world of Elastic MapReduce and the applications it can run is huge! Test your knowledge on a few of its finer points.

28
Machine Learning 101
29
Classification Models
30
Amazon ML Service
31
SageMaker
32
Note: Amazon Machine Learning Service is now deprecated!

If you have a new AWS account, you'll have to just watch the following exercise. But it's still important.

33
[Exercise] Amazon Machine Learning, Part 1

We'll use Amazon's Machine Learning service to predict quantities for any given order, and learn the importance of cleaning your data of outliers along the way.

34
[Exercise] Amazon Machine Learning, Part 2

Part 2 of our exercise to predict order quantities with a linear regression from Amazon ML.

35
Quiz: Amazon Machine Learning and SageMaker

Test your knowledge of details of Amazon ML and SageMaker that may prove useful in the exam.

36
Deep Learning 101
37
AWS Data Pipeline

Domain 4: Analysis

1
Section Introduction: Analysis
2
Intro to Kinesis Analytics
3
Kinesis Analytics Costs; RANDOM_CUT_FOREST
4
[Exercise] Kinesis Analytics, Part 1

We'll build up a more complex application that monitors our incoming order data using Kinesis Analytics. If an anomalous order rate is detected, an alarm will be sent via text message to your cell phone using Lambda and SNS.

5
[Exercise] Kinesis Analytics, Part 2

We'll build up a more complex application that monitors our incoming order data using Kinesis Analytics. If an anomalous order rate is detected, an alarm will be sent via text message to your cell phone using Lambda and SNS.

6
Quiz: Kinesis Analytics

Test your knowledge of the intricacies of Kinesis Analytics.

7
Intro to Elasticsearch
8
Amazon Elasticsearch Service
9
[Exercise] Amazon Elasticsearch Service, Part 1

In this hands-on activity, we'll spin up an Amazon Elasticsearch cluster, and configure Kinesis Firehose to dump Apache web server logs into it for querying and visualization with Kibana.

10
[Exercise] Amazon Elasticsearch Service, Part 2

In this hands-on activity, we'll spin up an Amazon Elasticsearch cluster, and configure Kinesis Firehose to dump Apache web server logs into it for querying and visualization with Kibana.

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