Description

Price: 15.00 USD | Size: 3.91 GB |   Duration : 19.56 Hours | 174 Video Lessons |

BRAND: Expert TRAINING | ENGLISH | INSTANT DOWNLOAD | 4.9

Going Pro Cloud Computing

Cloud Computing Foundations: From Zero to AutoML and Serverless Machine Learning in the Cloud

Learn AWS, Google and Azure clouds from absolute zero

This comprehensive course teaches you to leverage the power of cloud computing to develop production-ready machine learning solutions. Starting with the fundamentals of cloud storage, security, and infrastructure as code, you will gain a solid foundation in cloud computing concepts. The course then dives into serverless machine learning, teaching you to build and deploy ML models using popular cloud AutoML platforms like Google AutoML, Amazon SageMaker, Microsoft Azure ML, and CreateML. Through hands-on labs, you’ll learn to train custom models with just a few lines of configuration, without needing deep ML expertise.

Table of contents

1. Lesson 1
   1. “Instructor Intro”
   2. “Prerequisites”
   3. “Lab Onboarding”
   4. “Project Overview”
2. Lesson 2
   1. “Effective Tech Discussions Intro”
   2. “Effective Tech Discussions Technical Demo”
   3. “Demo Videos”
   4. “Effective Critical Thinking”
   5. “Effective Triple Threat”
   6. “Effective Technical Teamwork Intro”
   7. “Effective Technical Teamwork”
   8. “Intro”
   9. “Develop Effective Technical Project Management”
   10. “Trello”
   11. “Planning With Spreadsheets”
   12. “Anti Patterns”
3. Lesson 3
   1. “Intro”
   2. “What Is Ci”
   3. “Construct Project Scaffold”
   4. “Introduction Github Actions”
4. Lesson 4
   1. “Intro”
   2. “What Is Testing”
   3. “Introduce Azure Cloud Shell”
   4. “Azure Continuous Integration”
5. Lesson 5
   1. “Intro”
   2. “What Is Cd”
   3. “Gcp Cloud Shell”
   4. “Gcp Gae Deploy”
6. Lesson 6
   1. “Intro”
   2. “What Is Cloud Computing”
   3. “Cloud Computing Service Models”
7. Lesson 7
   1. “Static S3 Website”
   2. “Aws Lambda Website”
   3. “Aws Ec2”
   4. “Aws Elastic Beanstalk”
8. Lesson 8
   1. “Intro”
   2. “Cloud Computing Economics Story”
   3. “Cloud Economics”
9. Lesson 9
   1. “Intro”
   2. “Devops In The Real World”
   3. “Devops Practices”
   4. “Devops Best Practices”
10. Lesson 10
    1. “Intro”
    2. “Iac In The Real World”
    3. “What Is Iac”
    4. “Launch Vm Terraform”
11. Lesson 11
    1. “Intro”
    2. “Continuous Delivery Overview”
    3. “Continuous Delivery In Depth”
    4. “Continuous Delivery Hugo”
    5. “Azure App Deploy Pipelines”
    6. “Add Lint Azure Pipelines”
12. Lesson 12
    1. “Intro”
    2. “Project”
13. Lesson 13
    1. “Intro”
    2. “Containers Vm”
    3. “Spot Work”
    4. “Launch Spot”
    5. “Gcp Launch Vm”
    6. “Azure Create Compute Cluster”
14. Lesson 14
    1. “Intro”
    2. “When Containers”
    3. “What Is Docker”
    4. “Docker Hub”
    5. “Build Docker Container Scratch”
    6. “Push Container Aws”
15. Lesson 15
    1. “Intro”
    2. “Overview Kubernetes”
    3. “Deploy Kubernetes Gke”
    4. “Kubernetes Demo”
16. Lesson 16
    1. “Intro”
    2. “What Is Microservice”
    3. “Where Can You Run Microservices”
17. Lesson 17
    1. “Intro”
    2. “What Is Flask How To Use”
    3. “Change Microservice”
    4. “Flask Azure Microservice”
18. Lesson 18
    1. “Intro”
    2. “Serverless Functions How Work”
    3. “Marco Polo”
    4. “Marco Polo Step Function”
    5. “Aws Lambda S3 Trigger”
    6. “Aws Cli Trigger Lambda”
    7. “Google Cloud Function Change”
19. Lesson 19
    1. “Intro”
    2. “Alerts Monitoring”
    3. “Cloudwatch Demo”
    4. “Building Alert From Scratch”
20. Lesson 20
    1. “Intro”
    2. “Load Test”
    3. “Docker Flask Locust”
    4. “Prometheus”
21. Lesson 21
    1. “Intro”
    2. “Continuous Improvement”
    3. “Five Whys”
22. Lesson 22
    1. “Intro”
    2. “Project Overview”
23. Lesson 23
    1. “Intro”
    2. “Concurrency Python”
    3. “Understand Moores Law”
    4. “Using Cuda Numba”
    5. “What Is An Asic”
    6. “Colab Pro”
24. Lesson 24
    1. “Intro”
    2. “Cap Theorem”
    3. “Amdahl Law”
    4. “Elasticity”
    5. “Highly Available”
    6. “Debugging Python Code”
25. Lesson 25
    1. “Intro”
    2. “What Is Data Engineering”
    3. “Batch Events Streaming”
    4. “Building Cli With Click”
    5. “Building Containerized Cli”
    6. “Advanced Testing Techniques Code”
    7. “Functions Mapping To Cli”
26. Lesson 26
    1. “Intro”
    2. “What Is Serverless”
    3. “Serverless Concepts”
    4. “Build Serverless Data Engineering Pipeline”
    5. “Serverless Cookbook With Aws Gcp”
27. Lesson 27
    1. “Intro”
    2. “What Is Data Governance”
    3. “Cloud Security Iam”
    4. “Principle Least Privilage”
    5. “Aws Security”
    6. “Encrypt Transit Rest”
28. Lesson 28
    1. “Intro”
    2. “What Is Etl”
    3. “Etl Aws Glue Athena”
    4. “Real World Problems Etl”
29. Lesson 29
    1. “Intro”
    2. “One Size Doesnt Fit All”
    3. “Using Big Query”
    4. “Aurora Serverless Demo”
    5. “Dynamodb Demo”
    6. “Redshift Demo”
30. Lesson 30
    1. “Intro”
    2. “Why Cloud Storage”
    3. “Introduction Cloud Storage”
    4. “Using Amazon S3”
31. Lesson 31
    1. “Intro”
    2. “Project Overview”
32. Lesson 32
    1. “Intro”
    2. “What Is Ml Engineering”
    3. “Ml Engineering Architecture”
33. Lesson 33
    1. “Intro”
    2. “What Is Ml Microservice”
    3. “Monolithic Vs Microservice”
34. Lesson 34
    1. “Intro”
    2. “What Is Continuous Delivery For Ml”
    3. “Data Drift”
    4. “Walkthrough Flask Ml”
35. Lesson 35
    1. “Intro”
    2. “What Is Automl”
    3. “Automl Computer Vision”
36. Lesson 36
    1. “Intro”
    2. “What Is Automl”
    3. “Automl Computer Vision”
37. Lesson 37
    1. “Intro”
    2. “What Is Ludwig”
    3. “Ludwig Overview”
    4. “Ludwig By Example”
38. Lesson 38
    1. “Intro”
    2. “Cloud Automl Explained”
    3. “What Is Cloud Automl”
    4. “Azure Automl”
    5. “Nocode Lowcode Automl”
39. Lesson 39
    1. “Intro”
    2. “What Is Mlops”
    3. “Mlops Explained”
40. Lesson 40
    1. “Edge Intro”
    2. “What Is Edge Ml”
    3. “Edge Machine Learning In Action”
41. Lesson 41
    1. “Intro”
    2. “Use Ai Apis”
    3. “Using Ai Apis”