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AI Learning Path

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Learn AI basics with Azure and AWS
AWS Certified AI Practitioner
6h 0m
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Fundamentals of AI and ML
Fundamentals of Generative AI
Applications of Foundation Models
Guidelines for Responsible AI
Security
Compliance, and Governance for AI Solutions
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AI-900: Microsoft Certified Azure AI Fundamentals
4h 10m
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Fundamental AI Concepts
Fundamentals of Machine Learning
Introduction to Azure AI Services
Computer Vision
NPL
Azure NLP Services
Fundamentals of Azure OpenAI
generative AI
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Master prompts and AI-driven Kubernetes
Learn by Doing - Prompt Engineering 101
5h 0m
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Detailing for Clarity
Persona Play
Delimiters
Step-by-Step Clarification
Illustrating Through Examples
Specifying Output Length
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Introduction to K8sGPT and AI-Driven Kubernetes Engineering
1h 0m
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The AI Revolution in Kubernetes and DevOps
Introducing K8sGPT and AI Agents
The Future of DevOps Engineers
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Build advanced apps with AI
LangChain
5h 10m
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Overview of LangChain
Key Components of LangChain
Interacting with LLMs
Tips, Tricks, and Resources
ntroduction to LCEL
Adding Memory to LLM Apps
Performing Retrieval
implementing Chains
Using Tools
Building Agents
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Introduction to OpenAI
4h 10m
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Text generator
Advanced usage techniques
Content moderation
Image generation and captioning
Fine-tuning techniques
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Enhance coding with AI tools
AI-Assisted Development
6h 20m
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Introduction to AI-Assisted Development
Planning Phase
Development Phase - Backend
Development Phase - Frontend
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How long will it take for me to complete?

I can spend
hours / day
2
4
6
≈ 3 Months
≈ 2 Months
≈ 4 Months
≈ 2-3 Months
≈ 2-3 Months
≈ 1-2 Months
≈ 2-3 Months
≈ 2 Months
≈ 1 Months
≈ 1 Months
≈ 2 Months
≈ 1-2 Months
* This is based on averages from our students. This may change depending on your experience and level of expertise.

Success!!

Clear the KCNA exam with flying colors
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Test your Readiness for Free!

The skills test is a hands-on exam that helps you identify where you stand today in your preparation for your DevOps exam. Do you know about Git enough to attempt the exam? Find out now!

Topic based learning paths

Path

Linux

7 Courses
200h
Path

Programming

4 Courses
70h
Path

Kubernetes

9 Courses
183h
Path

Cloud

18 Courses
200h

Role based learning paths

Path

System
Administrator

13 Courses
341h
Path

Kubernetes
Administrator

12 Courses
250h
Path

DevOps
Engineer

17 Courses
350h
Path

Site Reliability
Engineer

13 Courses
320h
View All

FAQs

What is CI/CD?

CI/CD stands for Continuous Integration and Continuous Deployment. It is a set of practices and tools that enable developers to automatically build, test, and deploy software applications in a consistent and streamlined manner.

What is the difference between Continuous Integration and Continuous Deployment?

Continuous Integration (CI) focuses on automating the process of merging code changes from multiple developers into a shared repository and running automated tests to detect integration issues. Continuous Deployment (CD) takes CI a step further by automating the deployment of successfully tested code changes to production environments.

What are the benefits of implementing CI/CD?

CI/CD brings several benefits, including increased development speed, faster time to market, improved code quality, early bug detection, reduced manual errors, and easier collaboration among development teams.

What are some popular CI/CD tools?

Some popular CI/CD tools include Jenkins, GitLab CI/CD, CircleCI, Travis CI, TeamCity, and GitHub Actions. These tools provide automation capabilities for building, testing, and deploying applications.

How does CI/CD integrate with version control systems?

CI/CD tools integrate with version control systems, such as Git, to automatically trigger build and deployment processes whenever changes are pushed to the repository. This ensures that code changes are continuously tested and deployed.

What is the role of automated testing in CI/CD?

Automated testing is a crucial component of CI/CD. It includes unit tests, integration tests, and other types of automated tests that are executed as part of the CI/CD pipeline. These tests ensure the quality and reliability of the software before it is deployed.

Can CI/CD be used with containerized applications?

Yes, CI/CD is well-suited for containerized applications. Containers provide a consistent and reproducible environment for building, testing, and deploying applications, making it easier to integrate CI/CD pipelines into container-based workflows.

What are some common challenges in implementing CI/CD?

Some common challenges include managing complex deployment pipelines, ensuring compatibility across different environments, handling database migrations, maintaining good test coverage, and managing secrets and configurations securely.

Is CI/CD applicable only to cloud-based applications?

No, CI/CD can be applied to applications deployed in various environments, including on-premises, hybrid cloud, and multi-cloud environments. The principles of CI/CD can be adapted to different deployment scenarios.

What skills are important for implementing CI/CD?

Skills in version control systems (e.g., Git), scripting and automation (e.g., Bash, Python), knowledge of CI/CD tools, containerization (e.g., Docker), and infrastructure-as-code (e.g., Terraform) are valuable for successful implementation of CI/CD.