Free Udemy Course 2025: CISCO CCNP ENAUTO 300-435 - Free Udemy Course [100% Off]

Build a modern, job-ready automation mindset for enterprise networks with CISCO CCNP ENAUTO 300-435 ─ 1500 Exam Questions. This course is engineered to move you from 'I can script' to I can automate safely at scale. Every question is scenario-driven, so you will face real constraints: change windows, partial outages, rate limits, brittle credentials, inconsistent inventories, and the edge cases that break fragile automation in production.This is not a collection of random facts. It is a structured, exam-aligned system that trains the exact capabilities ENAUTO expects: APIs, Python, model-driven programmability, telemetry, controller platforms, and CI/CD-style validation. Your objective is to build repeatable engineering habits that keep the network stable while the business demands faster delivery and clearer evidence of change.During the first section, Automation Foundations, REST APIs & Auth Patterns — 250 Questions, you establish the logic that makes automation reliable. You learn to read API documentation quickly, understand resources and payloads, and predict how an endpoint will behave before you call it. Questions force you to reason about authentication choices, token scope, certificate trust, and how HTTP status codes translate into operational decisions. You also practice the less glamorous but critical skills: correct headers, content types, TLS verification, timeouts, and parsing error bodies to find the real root cause. By training idempotency and safe retries, you learn how to avoid accidental duplicate changes when a controller or network path is unstable.During the second section, Python for Network Automation: Data, Requests & Tooling — 250 Questions, you turn Python into a disciplined tool rather than a pile of lucky scripts. You work with structured data, safe JSON parsing, input validation, and modular design that other engineers can maintain. Scenarios push you toward patterns that scale: reusable functions, reliable logging, and guardrails that prevent destructive actions. You will be tested on building resilient request flows, handling exceptions cleanly, and using sessions to improve performance and consistency. You also practice practical team hygiene: dependency pinning, basic unit tests, mocking API calls, and safe credential handling so secrets never leak into Git history.During the third section, Model-Driven Networking: YANG, NETCONF, RESTCONF & gNMI — 250 Questions, you master the model-driven layer that separates modern automation from brittle CLI scraping. You practice reading YANG models, understanding containers, lists, keys, and leaf types, and mapping a model into correct JSON or XML payloads. Scenarios teach operational nuance: candidate vs running configuration, transactional edits, locks, capability discovery, and verification through operational state queries. You learn to recognize when an RPC action is better than a data-tree edit, and how to diff expected vs actual state after a change. By the end, model-driven automation stops being abstract and becomes a clear, predictable engineering workflow.During the fourth section, Controller Platforms: Catalyst Center, SD-WAN, ACI & Meraki APIs — 250 Questions, you build controller-driven thinking: intent, policy objects, and orchestrated change across many devices. You practice the patterns that repeat across platforms even when endpoints differ: inventory discovery, tagging and grouping, policy deployment, asynchronous job tracking, and post-change verification. Scenarios train you to avoid common controller mistakes such as automating against stale inventory, skipping readiness checks, or treating an asynchronous task as finished too early. You will also practice diagnosing controller-side failures: missing privileges, invalid scopes, partial reachability, and state inconsistencies that require careful, evidence-based troubleshooting.During the fifth section, Telemetry & Observability: Streaming Data, Logs, KPIs & Alerts — 250 Questions, you learn to automate with facts instead of guesses. You practice selecting signals that truly prove service health, choosing streaming telemetry vs polling, and designing KPIs that separate noise from real risk. Scenarios cover syslog, SNMP, NetFlow/IPFIX, controller events, and model-driven operational state, then ask you to decide what belongs in dashboards versus alerts. You will be pushed on root-cause reasoning: link loss vs congestion, control-plane churn vs data-plane drops, and intermittent 'brownout' symptoms that look random until the data is correlated. You also train telemetry pipeline decisions such as buffering, retention, and securing access in regulated environments.During the sixth section, CI/CD Validation: GitOps, Testing, Security & Reliable Rollouts — 250 Questions, you tie everything together into an engineered delivery system. You practice Git workflows, pull-request discipline, and pipelines that lint code, validate schemas, run tests, and execute dry-run checks before changes reach devices. Scenarios drill safe rollout strategy: canary changes, automated post-checks, maintenance windows, and rollback automation when verification fails. Security is not an afterthought here: you practice least privilege, token rotation, audit trails, and protecting automation under outages. You also train drift detection and define 'done' as verified state, not as a successful commit.How to use this course for maximum impact: treat each section like a production sprint. Do a timed attempt to expose weak spots, then review every explanation until you can describe the reasoning without looking. Retake the same section with a tighter target time, and repeat until your decision-making becomes calm and automatic. You can repeat the tests an unlimited number of times to reinforce and deepen your knowledge, and the question design is built to reward disciplined thinking rather than memorized phrases.If you are aiming to walk into ENAUTO 300-435 with real automation judgment and not just vocabulary, this course gives you a structured path: strong API reasoning, practical Python, correct model-driven payloads, controller workflows that scale, telemetry that proves health, and CI/CD validation that keeps change safe. That combination is what modern network teams expect, and it is exactly what this course trains you to deliver.