5 Courses Master AWS, Analytics, Machine Learning, Bigdata

5 Courses – Master AWS, Analytics, Machine Learning, Bigdata, available at $19.99, has an average rating of 3.9, with 68 lectures, based on 141 reviews, and has 13290 subscribers.

You will learn about Underastand Amazon Web Services, Migrate to Amazon Cloud, Machine learning and Data science This course is ideal for individuals who are For all those who is interested in learning about cloud Infrastructure, want to reap the benefits of migrating to AWS It is particularly useful for For all those who is interested in learning about cloud Infrastructure, want to reap the benefits of migrating to AWS.

Enroll now: 5 Courses – Master AWS, Analytics, Machine Learning, Bigdata

Summary

Title: 5 Courses – Master AWS, Analytics, Machine Learning, Bigdata

Price: $19.99

Average Rating: 3.9

Number of Lectures: 68

Number of Published Lectures: 68

Number of Curriculum Items: 68

Number of Published Curriculum Objects: 68

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Underastand Amazon Web Services, Migrate to Amazon Cloud, Machine learning and Data science

Who Should Attend

For all those who is interested in learning about cloud Infrastructure, want to reap the benefits of migrating to AWS

Target Audiences

For all those who is interested in learning about cloud Infrastructure, want to reap the benefits of migrating to AWS

5 courses pack including below topics.

# Course Lectures Duration (hh:mm:ss)

1 AWS – Cloud Services 27 05:38:02

Elastic Beanstalk,? ?ELB, ECS, EKS, Dynamo DB, Migration Hub? ?

2 AWS – Data Analytics 10 02:38:08

AWS Analytics and Data Lakes, Amazon Athena – Interactive query service, Amazon CloudSearch – Managed search service, Amazon Elasticsearch Service, Amazon Kinesis – Data Streams, Amazon Redshift – Data warehousing

Amazon QuickSight – Business Analytics Intelligence Service, Amazon Data Pipeline – Automate data movement, AWS Glue – Managed ETL Service?

3 BigData and Hadoop framework 14 01:20:13

Big data introduction, history, technologies, characteristics and Applications

Data Lake, Data science and Data scientist

Hadoop introduction, HDFS-Overview, Hadoop Architecture, assumptions and goals

Demo-Hadoop install – sw download verify integrity,? Java ssh configure,? Hadoop access by browser

4 Machine Learning 00:32:19

Introduction,? ?Algorithms, Softwares? ?

5 AWS Machine Learning 14 02:06:00

Bigdata and AWS, Hadoop on Amazon Elastic Map Reduce? –? ?EMR, Amazon EMR,?? Amazon EMR Architecutre, TensorFlow – Open source Machine Learning framework, Amazon SageMaker – TensorFlow Part 1 & 2, AWS Deep Learning AMIs, AWS Translate – Natual language translation, Amazon Polly – turn text to speech, Apache MXNet – Deep learning framework

TOTAL < 68 Lectures > 12hours 15min

Course Curriculum

Chapter 1: AWS Cloud Services

Lecture 1: Embrace Cloud computing

Lecture 2: AWS Products and Solutions

Lecture 3: AWS-Pricing – Simple Monthly calculator – TCO Calculator

Lecture 4: AWS Compute products and services

Lecture 5: Amazon Elastic Compute Cloud EC2

Lecture 6: Amazon EC2 – Dashboard

Lecture 7: Amazon EC2 – Launch Linux VM

Lecture 8: Amazon EC2 – Access Linux VM

Lecture 9: Amazon EC2 – Launch and access Windows server VM

Lecture 10: Amazon EC2 – Launch WordPress website

Lecture 11: AWS Elastic Beanstalk

Lecture 12: Amazon EC2 Autoscaling

Lecture 13: Elastic Load Balancing (ELB)

Lecture 14: Amazon Lightsail

Lecture 15: AWS Lamda

Lecture 16: AWS ECS using Fargate

Lecture 17: Storage – S3, EBS, EFS, Glacier, Snow Family, Gateway

Lecture 18: Storage S3 – create bucket, store retrieve files

Lecture 19: Access S3 through AWS – CLI with IAM user credentials

Lecture 20: Route 53, Domain name, DNS

Lecture 21: AWS Databases

Lecture 22: AWS – RDS MySQL – Create, connect and operate

Lecture 23: Amazon Dynamo DB

Lecture 24: Migration Hub

Lecture 25: Security, Identity, & Compliance

Lecture 26: AWS Step Functions

Lecture 27: Amazon CloudWatch monitoring and management service

Chapter 2: AWS Data Analytics

Lecture 1: AWS Analytics and Data Lakes

Lecture 2: Amazon Athena – Interactive query service

Lecture 3: Amazon CloudSearch – Managed search service

Lecture 4: Amazon Elasticsearch Service

Lecture 5: Amazon Kinesis – Data Streams – Visualizing Web Traffic Using Amazon Kinesis Dat

Lecture 6: Amazon Kinesis – Data Streams using AWS CLI

Lecture 7: Amazon Redshift – Data warehousing

Lecture 8: Amazon QuickSight – Business Analytics Intelligence Service

Lecture 9: Amazon Data Pipeline – Automate data movement

Lecture 10: AWS Glue – Managed ETL Service

Chapter 3: Bigdata and Hadoop framework

Lecture 1: 1.1 Big data introduction

Lecture 2: 1.2 Big data history

Lecture 3: 1.3 Big data technologies

Lecture 4: 1.4 Big data characteristics

Lecture 5: 1.5 Big data Applications

Lecture 6: 1.6 Data Lake

Lecture 7: 1.7 Data science and Data scientist

Lecture 8: 2.1 – Hadoop introduction

Lecture 9: 2.2 – HDFS-Overview

Lecture 10: 2.3 – Hadoop Architecture

Lecture 11: 2.3a – Hadoop Architecture – assumptions and goals

Lecture 12: 2.4 – Demo-Hadoop install – sw download verify integrity

Lecture 13: 2.5 – Demo-Hadoop install – Java ssh configure

Lecture 14: 2.6 Demo hadoop access by browser

Chapter 4: Machine Learning

Lecture 1: 3.1 Machine learning introduction

Lecture 2: 3.2 Machine learning algorithms

Lecture 3: 3.3 Machine learning softwares

Chapter 5: AWS Machine Learning

Lecture 1: 5.1 AWS and Machine learning

Lecture 2: 5.2 Bigdata and AWS

Lecture 3: 5.3 Hadoop on Amazon Elastic Map Reduce – EMR

Lecture 4: 5.4 Amazon Elastic MapReduce -EMR

Lecture 5: 5.5 Amazon EMR Architecutre

Lecture 6: 5.6 Amazon EMR benefits

Lecture 7: 5.7 Launch Amazon EMR cluster

Lecture 8: 5.8 TensorFlow – Open source Machine Learning framework

Lecture 9: 5.9 Amazon SageMaker – TensorFlow Part 1

Lecture 10: 5.9 Amazon SageMaker – TensorFlow Part 2

Lecture 11: 5.10 AWS Deep Learning AMIs

Lecture 12: 5.11 AWS Translate – Natual language translation

Lecture 13: 5.13 Amazon Polly – turn text to speech

Lecture 14: 5.14 Apache MXNet – Deep learning framework

Instructors

Kaushik Vadali
Cloud Infra and Info Security professional at CBTU

Rating Distribution

1 stars: 15 votes

2 stars: 27 votes

3 stars: 32 votes

4 stars: 41 votes

5 stars: 26 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!