The Ultimate DevOps Developer Roadmap
1 - Programming Languages
Pick and master one or two programming languages. Choose from options like Python, JavaScript, Go, Ruby, etc.
2 - Operating Systems
Master the ins and outs of major operating systems like Linux, Windows, Mac, and so on.
3 - Source Control Management
Learn about source control management tools such as Git, GitHub, GitLab, and Bitbucket.
4 - Networking
Master the basics of networking concepts such as DNS, IP, TCP, and SSH.
5 - CI/CD
Pick tools like GitHub Actions, Jenkins, or CircleCI to learn about continuous integration and continuous delivery.
6 - Scripting and Terminals
Learn scripting in bash, and PowerShell along with knowledge of various terminals and editors.
7 - Hosting and Platforms
Master multiple hosting platforms such as AWS, Azure, GCP, Docker, Kubernetes, Digital Ocean, Lambda, Azure Functions, etc.
8 - Infrastructure as Code
Learn infrastructure as code tools like Terraform, Pulumi, Ansible, Chef, Puppet, Kubernetes, etc.
@javascript_resources
9 - Monitoring and Logging
Master the key tools for monitoring and logging for infrastructure and applications such as Prometheus, Elasticsearch, Logstash, Kibana, etc.
10 - Basics of Software Development
Learn the basics of software development such as system availability, data management, design patterns, and team collaboration.
Over to you: What else would you add to this roadmap?
#devops #python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience
1 - Programming Languages
Pick and master one or two programming languages. Choose from options like Python, JavaScript, Go, Ruby, etc.
2 - Operating Systems
Master the ins and outs of major operating systems like Linux, Windows, Mac, and so on.
3 - Source Control Management
Learn about source control management tools such as Git, GitHub, GitLab, and Bitbucket.
4 - Networking
Master the basics of networking concepts such as DNS, IP, TCP, and SSH.
5 - CI/CD
Pick tools like GitHub Actions, Jenkins, or CircleCI to learn about continuous integration and continuous delivery.
6 - Scripting and Terminals
Learn scripting in bash, and PowerShell along with knowledge of various terminals and editors.
7 - Hosting and Platforms
Master multiple hosting platforms such as AWS, Azure, GCP, Docker, Kubernetes, Digital Ocean, Lambda, Azure Functions, etc.
8 - Infrastructure as Code
Learn infrastructure as code tools like Terraform, Pulumi, Ansible, Chef, Puppet, Kubernetes, etc.
@javascript_resources
9 - Monitoring and Logging
Master the key tools for monitoring and logging for infrastructure and applications such as Prometheus, Elasticsearch, Logstash, Kibana, etc.
10 - Basics of Software Development
Learn the basics of software development such as system availability, data management, design patterns, and team collaboration.
Over to you: What else would you add to this roadmap?
#devops #python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience
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Looking to level up your knowledge in Machine Learning (ML), Deep Learning (DL), and Artificial Intelligence (AI)?
Check out this comprehensive cheat sheet compiled by experts from Stanford University and MIT! It covers:
✅ Probability & Statistics – The backbone of ML & AI
✅ Supervised Learning – Linear regression, logistic regression, SVMs, and more
✅ Unsupervised Learning – Clustering, PCA, ICA, and dimensionality reduction
✅ Deep Learning – Neural networks, CNNs, RNNs, reinforcement learning
✅ Mathematical Foundations – Linear algebra, calculus, optimization
✅ ML Tips & Tricks – Model selection, performance metrics, and debugging
@javascript_resources
A must-have for anyone diving into AI, whether you're a beginner or a pro!
#MachineLearning #DeepLearning #ArtificialIntelligence #DataScience #AI #ML #DL #BigData #NeuralNetworks #Statistics #ComputerScience #Tech #Programming
Check out this comprehensive cheat sheet compiled by experts from Stanford University and MIT! It covers:
✅ Probability & Statistics – The backbone of ML & AI
✅ Supervised Learning – Linear regression, logistic regression, SVMs, and more
✅ Unsupervised Learning – Clustering, PCA, ICA, and dimensionality reduction
✅ Deep Learning – Neural networks, CNNs, RNNs, reinforcement learning
✅ Mathematical Foundations – Linear algebra, calculus, optimization
✅ ML Tips & Tricks – Model selection, performance metrics, and debugging
@javascript_resources
A must-have for anyone diving into AI, whether you're a beginner or a pro!
#MachineLearning #DeepLearning #ArtificialIntelligence #DataScience #AI #ML #DL #BigData #NeuralNetworks #Statistics #ComputerScience #Tech #Programming