All roadmapsRoadmap · 2026

MLOps Roadmap 2026

The complete MLOps roadmap in 7 stages — Foundational Knowledge, Core Machine Learning, MLOps Fundamentals, MLOps Tools & Platforms, Cloud & Infrastructure, Advanced MLOps & Best Practices and Projects & Job Preparation. Open any stage in the mind map to see the topics and tools inside it, or download the whole roadmap as an image.

Mind map

MLOps Roadmap

Click a topic to open or close it · drag to move · scroll to zoom · the download includes every topic, fully expanded

MLOps roadmap, stage by stage

01Foundational Knowledge
- Programming & Data Structures
  - Python Fundamentals
  - Data Structures & Algorithms
  - Object-Oriented Programming
- Mathematics & Statistics
  - Linear Algebra
  - Calculus
  - Probability & Statistics
- Machine Learning Basics
  - Supervised Learning
  - Unsupervised Learning
  - Model Evaluation
02Core Machine Learning
- ML Frameworks
  - Scikit-learn
  - TensorFlow
  - PyTorch
- Data Preprocessing
  - Feature Engineering
  - Data Cleaning
  - Handling Missing Data
- Model Training & Tuning
  - Hyperparameter Tuning
  - Cross-Validation
  - Regularization
03MLOps Fundamentals
- Version Control
  - Git
  - GitHub / GitLab
- Containerization

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Docker Basics

Docker Compose

CI/CD Concepts

Continuous Integration
Continuous Delivery
Continuous Deployment

04MLOps Tools & Platforms

ML Orchestration
- Kubeflow Pipelines
- Apache Airflow
- MLflow
Model Serving
- TensorFlow Serving
- TorchServe
- BentoML
Monitoring & Logging
- Prometheus
- Grafana
- ELK Stack
Feature Stores
- Feast
- Tecton

05Cloud & Infrastructure

Cloud Providers
- AWS (Sagemaker, EC2, S3)
- GCP (Vertex AI, GKE, GCS)
- Azure (Azure ML, AKS, Blob Storage)
Infrastructure as Code
- Terraform
- Ansible
Kubernetes
- Kubernetes Fundamentals
- Kubernetes Operations

06Advanced MLOps & Best Practices

Model Monitoring & Drift
- Data Drift Detection
- Concept Drift Detection
- Performance Monitoring
ML Security & Governance
- Model Explainability (SHAP, LIME)
- Bias Detection
- Access Control
Automated ML (AutoML)
- AutoML Libraries
- Hyperparameter Optimization Tools

07Projects & Job Preparation

End-to-End Projects
- Build & Deploy a Model
- Set up CI/CD for ML
- Implement Model Monitoring
Portfolio Building
- GitHub Portfolio
- Blog Posts / Case Studies
Job Search Skills
- Resume Optimization
- Interview Practice
- Networking