Course Calendar

Week 1

Cloud Computing Foundations-Part 1

Topics

  • Overview of Cloud Computing
  • Cloud Adoption Framework(s)
  • Economics of Cloud Computing
  • Develop non-linear life-long learning skills

Learning Objectives

  • Summarize the fundamentals of cloud computing
  • Evaluate the economics of cloud computing

Lectures

Readings/Media

Lab

Discussions/Assignments

  • What are the problems solved economically by cloud computing vs traditional infrastructure?
  • What skills are you going to learn by the end of this year, why and how?
  • What are the problems solved technically by cloud computing vs traditional infrastructure?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 2

Cloud Computing Foundations-Part 2

Topics

  • Cloud Service Models: SaaS, PaaS, IaaS, MaaS, Serverless
  • IaC (Infrastructure as Code) w/ Terraform
  • Continuous Delivery

Learning Objectives

  • Evaluate different cloud service paradigms (IaaS, MaaS,PaaS, SaaS, serverless) and choose the correct paradigm for the problem at hand.
  • Compose IAC (Infrastructure as Code) solutions

Lectures

Readings/Media

Lab

Discussions/Assignments

  • What is IAC and what problem does it solve?
  • How should a company decide on what level of cloud abstraction to use for a project: SaaS, PaaS, IaaS, MaaS, Serverless?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 3

Virtualization and Containers-Part 1

Topics

  • CPU, Memory, I/O
  • SDN (Software Defined Networks)
  • SDS (Software Defined Storage)

Learning Objectives

  • Summarize key components of virtualization: CPU, Memory and I/O
  • Summarize Software Defined Networks and Software Defined Storage

Readings/Media

Lab

  • AWS Educate Lab: Launch Spot Virtual Machine using AWS Deep Learning AMI into VPC and ssh to instance via Cloud9]
  • AWS Academy CloudFoundations Lab 4, 6: Build a Database Servers, Introduction to AWS IAM

Discussions/Assignments

  • What are the different layers of network security on AWS and what unique problems do each solve?
  • What problem do AWS Spot instances solve and how could you use them in your projects?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 4

Virtualization and Containers-Part 2

Topics

  • Containers: Docker, Kubernetes,
  • Hosted Services: EKS (Elastic Kubernetes Service), Google Kubernetes Engine,
  • Container Registries: Dockerhub, ECR, Google Container Registry

Learning Objectives

  • Create Docker format containers and recommend how to use them
  • Evaluate container management services like Kubernetes and hosted Kubernetes and create solutions with them
  • Summarize container registries and how to use them to create custom containers

Readings/Media

(Optional)

Lab

Discussions/Assignments

  • What are containers?
  • What problem do containers solve?
  • What is the relationship between Kubernetes and containers?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 5

Challenges and Opportunities in Distributed Computing -Part 1

Topics

  • CAP Theorem
  • Eventual Consistency
  • Amdahl’s law
  • High Availability
  • Fault Tolerance
  • Elasticity

Learning Objectives

  • Accurately evaluate distributed computing challenges and opportunities and apply this knowledge to real-world projects.
  • Summarize how eventual consistency places a role in Cloud-Native Applications

Readings/Media

Lab

  • AWS Academy Cloud Foundations Lab 5: Scale & Load Balance your Architecture

Discussions/Assignments

  • How does the CAP Theorem play a role in designing for the cloud?
  • What are the implications of Amdahl’s law for Machine Learning projects?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 6

Challenges and Opportunities in Distributed Computing-Part 2

Topics

  • End of Moore’s Law
  • ASICS: GPUs, TPUs, FPGAs

Learning Objectives

  • Recommend appropriate use cases for ASICS.
  • Consider the implications of the end of Moore’s Law

Readings/Media

Lab

Discussions/Assignments

  • How could ASICs play an important role in Machine Learning going forward?
  • Find, run and extend a notebook in seedbank and share along with your comments on what you learned.

Week 7

Cloud Storage-Part 1

Topics

  • Cloud Databases: HBase, MongoDB, Cassandra, DynamoDB, Google BigQuery

Learning Objectives

  • Evaluate different cloud service paradigms (IaaS, MaaS, PaaS, SaaS, serverless) and choose the correct paradigm for the problem at hand.
  • Compose IAC (Infrastructure as Code) solutions

Readings/Media

Lab

Discussions/Assignments

  • What are the problems with a “one size fits all” approach to relational databases?
  • How could a service like Google BigQuery change the way you deal with Data?
  • What problem does a “serverless” database like Athena solve?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 8

Cloud Storage-Part 2

Topics

  • Cloud Object Storage: Amazon S3, GCP Cloud Storage, Amazon Glacier, Data Lakes, OpenStack Swift
  • Distributed File Systems: Red Hat Ceph, Amazon EFS (Elastic File System), HDFS

Learning Objectives

  • Compare different types of cloud storage (Object, File System and Database) and know how to use them in the right context.

Readings/Media

(Optional)

Lab

  • (Optional if Available) AWS Academy Data Analytics Lab: Store data in Amazon S3, Query data in Amazon S3 with Amazon Athena and AWS Glue
  • Use the Cloud SDK Command Line

Discussions/Assignments

  • What are the key differences between block and object storage?
  • What are the key problems do a Data Lake solve?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 9

Serverless-Part1

Topics

  • Cloud 9 Development Environment
  • FaaS (Function as a Service): AWS Lambda, GCP Cloud Functions, Azure Functions
  • Cloud-Native Primitives: AWS Step Machines, AWS SQS, AWS SNS, AWS Cognito, AWS API Gateway

Learning Objectives

  • Design serverless applications (AWS Lambda, GCP Cloud Functions) and create cloud-native applications with them.

Readings/Media

(Optional)

Lab

  • [AWS Educate Lab: Build timed AWS lambda in Python with Cloud9]
  • (Optional if Available) AWS Academy Cloud Developing Lab: Module 10 - Lab 5: Developing with AWS Lambda and Amazon API Gateway

Discussions/Assignments

  • What are the tradeoffs with a serverless architecture?
  • How are the advantages to developing with Cloud9 ?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 10

Week-10: Serverless-Part2

Topics

  • Platform as a Service: Azure App Services, AWS Elastic Beanstalk and Google App Engine
  • Azure Cloud Shell Development Environment
  • Google Cloud Shell Development Environment
  • AWS Cloud9 Development Environment

Learning Objectives

  • Design PaaS applications Using Cloud-Native Tools

Readings/Media

Lab

Discussions/Assignments

  • What problems does Google App Engine solve?
  • What problems does the Cloud Shell environment solve?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 11

Big Data Platforms

Topics

  • Batch Processing: EMR/Hadoop, AWS Batch
  • ETL (Extract Transform Load): AWS Glue, AWS Athena
  • Stream Processing: EMR/Spark, AWS Kinesis, Kafka

Learning Objectives

  • Recommend Big Data technology and design Big Data technology solutions to real-world problems.

Readings/Media

(Optional)

Lab

Discussions/Assignments

  • What problems does Hadoop Solve?
  • What are the key differences between Hadoop and Spark?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 12

Managed Machine Learning Systems

Topics

  • AWS Sagemaker

Learning Objectives

  • Design big data machine learning solutions using Machine Learning platforms (AWS Sagemaker, GCP Big Query ML)

Readings/Media

(Optional)

Lab

Discussions/Assignments

  • What problems does Sagemaker solve?
  • What are competitive offerings to Sagemaker?
  • What is MLOps?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.

Week 13

Edge Computing

Topics

  • IoT: AWS Greengrass, Raspberry Pi
  • Edge Machine Learning: Tensorflow lite, Intel Movidius, Apple X12

Learning Objectives

  • Recommend edge computing technologies (IoT and edge ML Inference) to solve problems uniquely suited to the edge (privacy, latency, etc).

Readings/Media

Lab

Discussions/Assignments

  • What problems does edge-based machine learning solve?
  • What are the ML frameworks most widely used with edge inference?
  • Post a screenshot of a lab where you had difficulty with a concept or learned something.** **

Week 14

Final Project Demo