Python Programming for MLOps - AIOps - DevOps

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Manifold AI Learning ®

17:06:51

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1. Introduction to the Course

1. Welcome to the Course.mp4

04:01

2. What makes this course Unique.mp4

08:25

3.1 Source code and Slides.html

3. Source code access.html

2. Python Essentials for DevOps - MLOps - AIOps

1. Introduction to the Python.mp4

05:28

2. Introduction to Python.html

3. Installing and Running Python.mp4

08:47

4. Variables and Data Types in Python.mp4

06:11

5. Variables in Python.html

6. Jupyter Lab Interface Quick Tour.mp4

15:19

7. Varaibles and Data Types - Hands On.mp4

17:46

8. Variables in Python Quiz.html

9. Comments in Python Programming Language.mp4

07:02

10. Comments in Python.html

11. Operators in Python Programming.mp4

07:17

12. Operators in Python - Hands On.mp4

26:02

13. Operators in Python.html

14. Built-in Functions in Python Programming.mp4

04:06

15. Built-in Functions in Python Programming - Hands On.mp4

08:14

16. Built-in Functions in Python Programming - Part 2 - Hands On.mp4

09:23

17. Sequences in Python.mp4

05:15

18. Hands On Python Strings - Sequence Operations.mp4

08:02

19. Hands On Python List - Sequence Operations.mp4

03:51

20. Hands On Python Tuple - Sequence Operations.mp4

03:03

21. Hands On Python Dictionary - Sequence Operations.mp4

02:45

22. Hands On Python Sets - Sequence Operations.mp4

05:31

23. Hands On Python Range - Sequence Operations.mp4

01:54

24. Execution Control in Python.mp4

06:29

25. Hands On Conditional Statements in Python.mp4

14:28

26. Hands On For - Control Statements in Python.mp4

07:08

27. Hands On While - Control Statements in Python.mp4

05:56

28. Hands On Loop Control Statements in Python Programming.mp4

07:24

29. Exception Handling in Python.mp4

07:50

30. String Formatting in Python.mp4

04:09

31. String Formatting - Hands On.mp4

05:38

32. User Defined Functions in Python.mp4

08:35

33. User Defined Functions & Scope of Variables Hands On.mp4

21:45

34. Anonymous Functions - Lambda.mp4

05:03

35. Advanced Functions - map, filter, list & dict comprehension.mp4

06:24

36. Modules in Python.mp4

08:18

37. Mudules in Python - Hands On.mp4

13:38

38. Regular Expressions.mp4

09:30

39. Regular Expressions Hands On.mp4

16:27

40. Introduction to Object Oriented Python.mp4

07:20

41. Hands On - Classes and Objects.mp4

21:02

42. Object Oriented Concepts in Python.mp4

02:49

43. Section Summary.mp4

18:37

44. Object Oriented Concepts - Hands On.mp4

02:12

3. Python File Automation - working with Files and Filesystem

1. Introduction to Python File Automation.mp4

02:03

2. Working with Files and Directory.mp4

04:40

3. Working with Text files.mp4

14:07

4. Working with Binary Files.mp4

05:07

5. Working with Common File formats in DevOps - MLOps AIOps Projects.mp4

13:21

6. Working with Common File formats in DevOps - MLOps AIOps Projects - Part 2.mp4

11:19

7. Strategies for working with Large Files.mp4

05:50

8. Encryption and Cryptography using Python.mp4

16:02

9. Working with Directories in Python - os, shutil, pathlib.mp4

10:30

10. Examples from MLOps.mp4

05:02

4. Command Line Automation - DevOps - MLOps - AIOps

1. Introduction to Working with Command Lines.mp4

06:10

2. Working with sys module - Hands On.mp4

05:11

3. Working with os module.mp4

02:59

4. Working with subprocess module.mp4

06:42

5. Working with Command Line tools.mp4

08:40

6. sys.argv - command line inputs.mp4

13:45

7. Argparse - Parsing Command Line inputs.mp4

13:52

8. Function Decorators.mp4

12:59

9. Parsing the Command line using Click.mp4

13:58

10. Creating a More Complex CLI using Click.mp4

10:25

11. Working with fire package.mp4

11:59

5. Linux Utilities with Python

1. Introduction to Python Fabric Library.mp4

05:44

2. Hands On Python Fabric.mp4

09:04

3. Monitor the System with psutil.mp4

03:48

4. Hands On psutil.mp4

01:41

6. Python Package Management

1. Introduction to Python Package Management.mp4

09:37

2. Hands on Package Management with Python.mp4

20:56

3. Hands On MLOps Package to pypi.mp4

08:11

7. Docker for DevOps - MLOps - AIOps

1. Introduction to DevOps.mp4

08:15

2. Introduction to Docker.mp4

07:10

3. Docker Installation.mp4

02:09

4. Docker Hands On.mp4

18:56

8. Github Actions for Python Projects

1. Introduction to GitHub Actions.mp4

06:19

2. Quick Demo on github actions YAML file.mp4

10:41

3. Understanding github Actions YAML file.mp4

05:41

4. Create github Actions from Scratch.mp4

09:37

5. Configure Workflow based on use case.mp4

03:48

9. Getting Started with AWS - Prep work for CI CD Pipeline - Python Projects

1. Agenda of the Section.mp4

01:52

2. Create AWS Account.mp4

04:18

3. Setting up MFA on Root Account.mp4

08:09

4. Create IAM Account and Account Alias.mp4

07:08

5. Setup CLI with Credentials.mp4

04:48

6. IAM Policy.mp4

02:42

7. IAM Policy generator & attachment.mp4

07:44

8. Delete the IAM User.mp4

01:11

9. S3 Bucket and Storage Classes.mp4

14:39

10. Creation of S3 Bucket from Console.mp4

07:50

11. Creation of S3 Bucket from CLI.mp4

04:52

12. Version Enablement in S3.mp4

06:17

13. Introduction EC2 instances.mp4

04:21

14. Launch EC2 instance & SSH into EC2 Instances.mp4

08:40

15. Clean Up Activity.mp4

00:49

10. CI CD Pipeline with Github Actions - AWS EC2 Instances

1. Agenda of the Section.mp4

01:33

2. Exploring the files of CI CD Python.mp4

10:56

3. Pre-requisite setup for ci cd pipeline.mp4

14:36

4. Test the CI CD with AWS.mp4

06:03

11. Pytest for MLOps - AIOps

1. Introduction to Pytest.mp4

06:57

2. pytest Hands on.mp4

14:24

3. pytest fixtures.mp4

08:13

12. Infrastructure Automation using Python

1. Introduction to IAAC.mp4

04:46

2. Introducing Pulumi.mp4

05:09

3. Getting System rReady.mp4

05:51

4. Pulumi Hands On.mp4

14:33

5. Pulumi with Advanced Use case - EC2 with Security Group.mp4

05:35

13. Python for MLOps - AIOps

1. Introducing MLOps.mp4

07:13

2. Hands On Demo MLOps.mp4

12:56

3. Testing the MLOps.mp4

02:34

14. Monitoring and Logging with Python

1. Introduction to Continuous Monitoring.mp4

08:21

2. Use case on Continuous Monitoring.mp4

03:40

3. Introduction to Prometheus.mp4

04:28

4. Architecture of Prometheus.mp4

11:38

5. Metric Types of Prometheus.mp4

03:49

6. Installation of Prometheus.mp4

14:06

7. Introduction to Grafana.mp4

02:02

8. Installation of Grafana.mp4

04:54

9. Prometheus Configuration file.mp4

07:12

10. Exploring the Basic Querying Prometheus.mp4

08:04

11. Monitor the Infrastructure with Prometheus.mp4

02:45

12. Monitor the Linux Server with Node Exporter.mp4

10:07

13. Monitor the Client Application using Prometheus.mp4

04:20

14. Monitor the FastAPI Application using Prometheus.mp4

10:09

15. Monitor All EndPoints using Prometheus.mp4

07:29

16. Create Visualization with Grafana.mp4

18:00

17. Trigger Alerts with Grafana.mp4

13:46

Description

Optimize MLOps, AIOps, and DevOps Workflows with Python

What You'll Learn?

Apply Python confidently to infrastructure and operations tasks: Write clean, modular Python code using core principles, file handling, modules, and OOP.
Automate file-related operations: Efficiently manipulate, encrypt, and work with various file formats commonly used in DevOps, MLOps, and AIOps.
Create interactive command-line applications: Build CLIs with Python to automate tasks and streamline workflows.
Effectively manage Linux systems remotely: Use Python's Fabric library for remote execution and psutil for system monitoring
Create, manage, and publish Python packages: Organize code into reusable packages and distribute them on platforms like PyPI.
Utilize Docker for application deployments: Understand Docker image creation, containerization, and deployment.
Automate workflows with GitHub Actions: Design and configure CI/CD pipelines using GitHub Actions.
Implement CI/CD workflows utilizing AWS services: Design pipelines that leverage S3 for storage and EC2 instances for deployment.
Write tests specifically for MLOps projects: Ensure MLOps reliability and maintainability using Pytest.
Provision and manage infrastructure using code: Apply Infrastructure as Code (IaC) principles with Pulumi's Python SDK.
Experience a complete MLOps pipeline: Build an end-to-end MLOps solution integrating tools and concepts learned throughout the course.
Set up continuous monitoring for improved visibility: Implement monitoring and alerting using Prometheus and Grafana.

Who is this for?

Developers interested in streamlining DevOps processes

Data scientists and ML engineers looking to enhance MLOps practices

IT professionals wanting to implement AIOps strategies

Anyone eager to master Python for infrastructure management and automation

What You Need to Know?

No Programming Experience is needed

Just a Laptop and CLI to code

More details

Description
Master the essential Python skills you need to streamline DevOps workflows, implement intelligent MLOps pipelines, and optimize AIOps practices. This comprehensive course dives into Python fundamentals, file automation, command-line mastery, Linux utilities, package management, Docker, CI/CD with AWS, infrastructure automation, and even advanced monitoring and logging techniques.
Key Skills You'll Develop:
Python Foundations: Get a robust understanding of variables, data types, control structures, functions, object-oriented programming, and best practices for clean Python code.
File Automation: Effortlessly manipulate text, binary, and various file formats (like CSV, JSON, and more) used in MLOps, AIOps, and DevOps projects. Learn encryption strategies for secure file handling.
Command-Line Power: Build command-line interfaces and automate tasks with Python libraries like argparse, Click, and fire.
Linux Integration: Interact with Linux systems effectively using Python's Fabric and psutil libraries.
Package Management: Learn to create, manage, and publish your own Python packages to streamline your workflows.
Docker Expertise: Master Docker containerization for consistent and portable deployments.
GitHub Actions Automation: Create and customize GitHub Actions workflows for your Python projects.
AWS Essentials: Set up your AWS environment, work with S3 buckets, manage EC2 instances, and design CI/CD pipelines on AWS.
Pytest Power: Write robust and maintainable tests for your MLOps projects using Pytest.
Infrastructure as Code with Pulumi: Automate infrastructure provisioning and management using Pulumi's Python SDK.
MLOps in Action: Participate in a hands-on demo showcasing a complete MLOps pipeline.
Monitoring & Logging: Set up continuous monitoring with Prometheus and Grafana for actionable insights into your systems.
Who This Course Is For:
Developers interested in streamlining DevOps processes
Data scientists and ML engineers looking to enhance MLOps practices
IT professionals wanting to implement AIOps strategies
Anyone eager to master Python for infrastructure management and automation
Who this course is for:
Developers interested in streamlining DevOps processes
Data scientists and ML engineers looking to enhance MLOps practices
IT professionals wanting to implement AIOps strategies
Anyone eager to master Python for infrastructure management and automation

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Manifold AI Learning ® is an online Academy with the goal to empower the students with the knowledge and skills that can be directly applied to solving the Real world problems in Data Science, Machine Learning and Artificial intelligence.Checkout our instructor profile for the complete list of courses.All the best for your Learning.- Team ManifoldAILearning ®"Learn the Future"

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