Automate reproducible ML pipelines, model delivery and monitoring.
Explore now. Upload and review a resume to personalize alignment.
Analyze a resumeIntermediate → advanced · 600–1200 focused hours of overlapping study and project practice. Job-readiness development is ongoing.
Editorial planning ranges based on curriculum scope—not measured universal learning times. Prior knowledge and practice quality change the journey.
No skills in this group.
An absent mention does not mean you do not know a skill.
Mark skills as Learning below to track your focus.
Self-marked Learning, not an inferred proficiency rating.
An absent mention does not mean you do not know a skill.
Resume detection never automatically completes a skill. Progress stays in this browser and is shared across career paths.
Suggested next step: Python →Python is a general-purpose programming language.
60–120 focused hours · roughly 6.0–12.0 weeks at your schedule · Beginner
Prerequisites: No specific prerequisite.
Milestone: Build a CSV reporting command-line tool.
Linux is an operating-system family with useful server tools.
25–60 focused hours · roughly 2.5–6.0 weeks at your schedule · Beginner
Prerequisites: No specific prerequisite.
Milestone: Diagnose a failed service in an isolated virtual machine.
Git records changes to source code.
8–16 focused hours · roughly 0.8–1.6 weeks at your schedule · Beginner
Prerequisites: No specific prerequisite.
Milestone: Track a small project and resolve a practice merge conflict.
Networking explains how systems communicate.
40–80 focused hours · roughly 4.0–8.0 weeks at your schedule · Beginner
Prerequisites: No specific prerequisite.
Milestone: Explain a DNS and HTTP trace in a local lab.
Testing verifies expected software behavior.
25–50 focused hours · roughly 2.5–5.0 weeks at your schedule · Beginner
Prerequisites: No specific prerequisite.
Milestone: Design API cases including invalid requests and ownership; learn Python before the unittest coding exercises.
NumPy provides efficient numerical arrays.
20–40 focused hours · roughly 2.0–4.0 weeks at your schedule · Beginner
Prerequisites: Python
Milestone: Implement vectorized dataset summaries.
Pandas manipulates tabular data in Python.
25–50 focused hours · roughly 2.5–5.0 weeks at your schedule · Beginner
Prerequisites: Python
Milestone: Clean a messy sales dataset with an audit report.
Statistics helps reason about data and uncertainty.
60–120 focused hours · roughly 6.0–12.0 weeks at your schedule · Beginner
Prerequisites: No specific prerequisite.
Milestone: Compare two groups and explain uncertainty and confounders.
ML learns patterns from examples rather than fixed rules.
100–200 focused hours · roughly 10.0–20.0 weeks at your schedule · Intermediate
Prerequisites: Python · NumPy · Statistics
Milestone: Compare a baseline and classifier on held-out data.
Model evaluation checks performance and failure modes.
30–60 focused hours · roughly 3.0–6.0 weeks at your schedule · Intermediate
Prerequisites: Machine Learning
Milestone: Write an error-analysis report with limitations.
Docker packages applications into containers.
25–50 focused hours · roughly 2.5–5.0 weeks at your schedule · Beginner
Prerequisites: Linux
Milestone: Containerize a small API with a persistent database.
MLflow records experiments and manages model artifacts.
35–70 focused hours · roughly 3.5–7.0 weeks at your schedule · Intermediate
Prerequisites: Machine Learning · Python
Milestone: Track experiments and document a model promotion decision.
An API exposes data and operations through defined requests.
20–45 focused hours · roughly 2.0–4.5 weeks at your schedule · Beginner
Prerequisites: No specific prerequisite.
Milestone: Design an inventory CRUD API with failure cases.
Model serving exposes trained models for prediction.
40–80 focused hours · roughly 4.0–8.0 weeks at your schedule · Intermediate
Prerequisites: Machine Learning · REST API · Docker
Milestone: Serve a model with input validation and latency tests.
CI/CD automates safe build, test and release workflows.
30–60 focused hours · roughly 3.0–6.0 weeks at your schedule · Intermediate
Prerequisites: Git · Testing
Milestone: Create a test-and-build pipeline with a manual release gate.
ML pipelines connect repeatable data and model operations.
60–120 focused hours · roughly 6.0–12.0 weeks at your schedule · Advanced
Prerequisites: MLflow · CI/CD · Model Evaluation
Milestone: Automate a validated training-to-registry workflow.
Cloud fundamentals explain on-demand computing services.
35–70 focused hours · roughly 3.5–7.0 weeks at your schedule · Beginner
Prerequisites: Networking
Milestone: Compare two cloud architecture options on paper.
AWS supplies cloud infrastructure and managed services.
40–90 focused hours · roughly 4.0–9.0 weeks at your schedule · Beginner
Prerequisites: Networking
Milestone: Design a small deployment and budget before provisioning anything.
Terraform describes infrastructure as code.
35–70 focused hours · roughly 3.5–7.0 weeks at your schedule · Intermediate
Prerequisites: Cloud Fundamentals
Milestone: Plan a small infrastructure module without creating billable resources.
Kubernetes orchestrates container workloads.
60–120 focused hours · roughly 6.0–12.0 weeks at your schedule · Advanced
Prerequisites: Docker · Linux · Networking
Milestone: Deploy a local app and practice a rollback.
Monitoring tracks system behavior and failures.
30–60 focused hours · roughly 3.0–6.0 weeks at your schedule · Intermediate
Prerequisites: Linux · Networking
Milestone: Instrument a local API and write an actionable alert.
Record data versions, parameters, metrics and artifacts.
Skills practiced: MLflow · Model Evaluation
Add quality checks and a model promotion gate.
Skills practiced: ML Pipelines · CI/CD
Version an inference service and exercise rollback/drift alerts locally.
Skills practiced: Model Serving · Kubernetes · Monitoring
Career recommendations and learning timelines are educational guidance based on your resume and selected goals. They are not guarantees of employment or professional competency. Timelines vary; external resources can change. Skill guides link the source curricula used to plan this path.