mcAfee Secure Website
23

Cisco 200-301 Bundle

Exam Code: 200-301

Exam Name Cisco Certified Network Associate (CCNA)

Certification Provider: Cisco

Corresponding Certification: CCNA

200-301 Training Materials $44.99
Pass4sure Q&A Sample #1 Pass4sure Q&A Sample #2 Pass4sure Q&A Sample #3 Pass4sure Q&A Sample #4 Pass4sure Q&A Sample #5 Pass4sure Q&A Sample #6 Pass4sure Q&A Sample #7 Pass4sure Q&A Sample #8 Pass4sure Q&A Sample #9 Pass4sure Q&A Sample #10

Reliable & Actual Study Materials for 200-301 Exam Success

The Latest 200-301 Exam Questions as Experienced in the Actual Test!

  • 24
    Questions & Answers

    200-301 Questions & Answers

    760 Questions & Answers

    Includes questions types found on actual exam such as drag and drop, simulation, type in, and fill in the blank.

  • 25
    200-301 Video Course

    200-301 Training Course

    271 Video Lectures

    Based on Real Life Scenarios which you will encounter in exam and learn by working with real equipment.

  • exam =30
    Study Guide

    200-301 Study Guide

    1969 PDF Pages

    Study Guide developed by industry experts who have written exams in the past. They are technology-specific IT certification researchers with at least a decade of experience at Fortune 500 companies.

exam =32

Cisco Certified Network Associate (CCNA) (200-301) Practice Tests

Guarantee

Satisfaction Guaranteed

Pass4sure has a remarkable Cisco Candidate Success record. We're confident of our products and provide no hassle product exchange. That's how confident we are!

99.3% Pass Rate
Total Cost: $194.97
Bundle Price: $149.98

Purchase Individually

  • exam =34
    Questions & Answers

    Questions & Answers

    760 Questions

    $124.99
    exam =35
  • exam =37
    200-301 Video Course

    Training Course

    271 Video Lectures

    $39.99
  • exam =36
    Study Guide

    Study Guide

    1969 PDF Pages

    $29.99

Cisco 200-301 Practice Test 58

Question 570

An engineer trains an ML model to forecast interface congestion and reports 99% accuracy by testing on the same time windows used for training. What is the primary concern?

  1. The model must be correct because the training data was collected from production interfaces.
  2. No evaluation is needed if the interface has a known device hostname.
  3. Only model file size determines whether congestion forecasts will be accurate.
  4. Training-set evaluation can overestimate generalization; validate on held-out time periods with representative traffic conditions.

Explanation

Correct Answer

D:

An ML model can memorize particular training patterns without predicting a later traffic surge reliably. A separated evaluation period better tests performance on unseen load and helps identify leakage from future observations. The engineer should compare useful forecast metrics and operational consequences rather than citing in-sample accuracy alone.

Incorrect Answers

A:

Production-origin data can still be overfit. Authentic measurements do not replace an independent evaluation period.

B:

Names identify devices but do not establish forecast reliability. A held-out time period and real congestion outcomes are the needed test.

C:

Disk size and parameter count do not demonstrate predictive generalization. The case requires measuring unseen traffic outcomes.

Question 571

A campus network team wants to generate brief natural-language summaries of reviewed incident timelines for operators while keeping raw event logs immutable. Which AI role is most suitable?

  1. Apply the summary text directly as a router configuration file.
  2. Use generative AI to summarize the supplied verified incident facts, with citations and human checking before operational action.
  3. Use a model to overwrite the raw logs with its summarized account and discard timestamps.
  4. Assume a generated explanation is proof of the incident root cause without checking device data.

Explanation

Correct Answer

B:

Generative AI can transform lengthy reviewed incident notes and logs into a readable narrative. Grounding in actual event data and verifying citations helps prevent fabricated symptoms or causal claims from entering the record. The model should not alter preserved logs, close incidents or execute a configuration change without authorization.

Incorrect Answers

A:

Natural-language incident summaries do not provide a validated executable configuration. Applying them as commands is unrelated and could disrupt network services.

C:

A summary is a derived interpretation, not a replacement for original evidence. Overwriting log records destroys details needed for audit and root-cause reconstruction.

D:

Generative models can produce plausible but unsupported narratives. Root-cause assertions need corroboration with logs, topology, packet counters and change records.

Question 572

An NOC team does not have labeled examples of every possible new fault but wants to group unusually similar syslog-event patterns for investigation. Which approach is suitable?

  1. Turn off syslog to avoid generating too many clusters during troubleshooting.
  2. Unsupervised grouping or anomaly detection over normalized event features, followed by operator investigation.
  3. Send all events to a text-to-speech synthesizer and classify faults by playback duration.
  4. Require a supervised label for every unknown fault before the system may group the messages.

Explanation

Correct Answer

B:

Unsupervised models can identify recurring patterns or outliers without requiring a labeled example of every fault type. Their clusters are exploratory signals, not proof that a specific root cause occurred. Operators should correlate results with timestamps, device health and change history before raising a confirmed incident.

Incorrect Answers

A:

Removing event records discards the signals the model needs. It also weakens incident investigation rather than identifying recurring anomalous patterns.

C:

Speech rendering converts event text into audio; it does not discover statistical grouping in the event features. Audio duration does not provide a fault taxonomy.

D:

Labeled learning is useful when ground truth exists, but the scenario explicitly lacks labels for emerging faults. Unsupervised grouping can still surface candidate patterns.

Question 573

A network fault-prediction model has performed well for months but begins missing incidents after a major routing architecture change. Historic training telemetry no longer represents normal operation. What should the team address?

  1. Keep the model unchanged because successful historical training guarantees future precision.
  2. Delete all change records so the model cannot notice the architecture migration.
  3. Raise every interface bandwidth value in the monitoring dashboard so prior model thresholds appear satisfied.
  4. Evaluate data or concept drift and retrain or recalibrate the model using representative post-change telemetry.

Explanation

Correct Answer

D:

Prediction quality can degrade when the relationships between observed metrics and real faults change. A new routing design can alter baselines, feature distributions and the meaning of alarms. The team should compare new labeled outcomes against predictions, update data and evaluate the revised model before relying on automated escalation.

Incorrect Answers

A:

Past validation applies to the distribution used at the time. New topology and traffic patterns can invalidate the feature-to-outcome relationship.

B:

Change history helps explain the timing and nature of drift. Hiding it prevents useful troubleshooting and does not restore prediction accuracy.

C:

Changing dashboard labels does not repair a model trained on an obsolete distribution. It can mask genuine issues and contaminate operational evidence.

Question 574

A network AI alert flags 200 potential microbursts, but a review reveals many routine scheduled backup transfers are classified as incidents. What is the most appropriate evaluation change?

  1. Convert the backups to an additional DNS zone and retain the same alert model.
  2. Declare all 200 alerts correct because the classifier generated them with a high numeric score.
  3. Disable burst telemetry entirely while keeping the classifier running on unchanged inputs.
  4. Measure false positives on representative backup periods and refine the model features, labels or operating threshold.

Explanation

Correct Answer

D:

A high alert count does not establish good precision if normal backups trigger incidents. The team should compare predictions with reviewed ground truth, test precision and recall for the incident class, and tune sensitivity with business impact in mind. Maintaining a record of false alarms helps improve confidence without suppressing genuine microbursts.

Incorrect Answers

A:

DNS organization has no direct effect on classification of interface telemetry. The false positive problem requires evaluating the observed traffic data and model behavior.

B:

A confidence score is not ground truth and can be miscalibrated. Reviewed normal backup periods are direct evidence that some alarms were false positives.

C:

Removing measurements loses evidence and makes the detection task less reliable. It does not address the feature or threshold reason for misclassification.

Question 575

A security team has accurately labeled historical network flows as benign or malicious and wants a model that predicts one of those known labels for new flow records. Which ML approach fits the training data?

  1. Use only a static device banner to assign each new flow a threat category.
  2. Supervised learning using the labeled flows and a held-out evaluation set.
  3. Unsupervised clustering with no use of the supplied labels as ground truth.
  4. Generate random JSON labels and report agreement with those synthetic labels as accuracy.

Explanation

Correct Answer

B:

The dataset provides ground-truth labels that a supervised classifier can learn to associate with observed flow features. Hold-out validation should examine false positives and missed attacks, particularly under class imbalance. The labels do not make every future inference correct, so the system still needs monitoring and analyst review.

Incorrect Answers

A:

Device banners are administrative text and do not analyze packet-flow features. The problem asks for a trained inference over recorded labeled behaviors.

C:

Clustering groups similar observations without learning the specified benign/malicious label mapping. It may help exploration, but it does not directly fit the labeled classification requirement.

D:

Synthetic random labels are not the reviewed security outcomes in the historical dataset. Agreement with them cannot establish a useful classifier.

Question 576

A controller API endpoint accepts JSON documents, but an engineer sends a valid JSON payload marked as `Content-Type: text/plain`; the service rejects the media type. What should change?

  1. Rename the JSON file to config.txt without changing the request headers or payload.
  2. Change only the HTTP Accept header to text/plain while leaving Content-Type wrong.
  3. Use the API-documented `Content-Type: application/json` header with the valid JSON body.
  4. Change the network switch port from trunk to access mode to fix JSON parsing.

Explanation

Correct Answer

C:

Content-Type identifies the media type of the submitted representation, allowing the server to select the correct parser. An endpoint expecting JSON may reject text/plain even if the body bytes resemble JSON. The client should use the documented schema, UTF-8 encoding and secure transport rather than change unrelated device interfaces.

Incorrect Answers

A:

A filename extension does not determine the HTTP entity media type sent to a REST service. The server reads the request headers and body.

B:

Accept expresses a preferred response representation, not the format of the request body being sent. It does not repair the incorrect payload media type.

D:

Layer 2 switchport configuration is unrelated to an application-layer media-type rejection. The HTTP payload declaration is the actual failure.

Question 577

An automation client must update just the `description` property on one supported switch interface while preserving the other fields. The API explicitly documents PATCH for partial updates. Which method should it use?

  1. Submit an authenticated PATCH payload changing the description field only, using the API’s required patch encoding.
  2. Use DELETE to remove the old description and assume the server infers a replacement from nothing.
  3. Use GET with the new description and assume the controller writes it automatically.
  4. Use a full replacement PUT with only the description object and assume every omitted property remains unchanged.

Explanation

Correct Answer

A:

PATCH is defined for applying a partial modification to a target resource, which matches changing one property without replacing the full object. The engineer must use the precise supported media type and JSON or YANG patch schema. They should then read back the resource to confirm that other configuration values were preserved.

Incorrect Answers

B:

DELETE normally removes a resource, not set an arbitrary new field. The desired updated value must be provided in a supported patch request.

C:

GET is for retrieving state, not a partial configuration edit. Adding new text to a read request does not create write semantics.

D:

An endpoint may treat PUT as full replacement, which can reset unspecified fields. The case explicitly supports PATCH for the desired targeted change.

Question 578

An automation client sends a controller API request without an accepted authentication token and receives HTTP 401. Which interpretation and action are appropriate?

  1. HTTP 401 proves the resource URI does not exist; create it before authenticating.
  2. HTTP 401 means the server successfully created the resource and needs no further checks.
  3. Disable HTTPS to allow a rejected bearer token to be sent more easily over HTTP.
  4. The request lacks valid authentication; obtain or refresh the approved credential and retry only with authorized access.

Explanation

Correct Answer

D:

HTTP 401 indicates the request has not been applied because it lacks valid authentication credentials for the requested resource. A client may need an access token of the correct audience or an unexpired session. Credentials should be transmitted securely and protected, never logged in cleartext to troubleshoot the issue.

Incorrect Answers

A:

Not Found is commonly represented by 404. The supplied 401 response concerns authentication and does not establish the resource’s existence or absence.

B:

A successful creation commonly uses 201, not 401. An unauthorized request cannot be treated as proof that a write succeeded.

C:

Removing transport security exposes authentication material and does not correct an invalid or missing credential. Authentication should be repaired within the supported secure API contract.

Question 579

A controller API documents PUT as replacing a configuration resource at its full URI. The client wants to submit a complete desired representation rather than modify one field. Which method matches that contract?

  1. Send PUT to the existing resource URI with the complete valid representation and verify the response.
  2. Use PATCH but assume it always replaces all unspecified fields by definition.
  3. Use GET with a JSON body to replace the existing configuration.
  4. Use OPTIONS and assume it automatically writes the desired resource object.

Explanation

Correct Answer

A:

PUT is commonly used to create or replace the resource state identified by the target URI according to the API contract. Supplying the full intended representation avoids accidentally omitting fields that replacement semantics could remove. The network engineer should still verify server-specific rules, authentication and configuration validation.

Incorrect Answers

B:

PATCH expresses partial modifications and its exact patch document semantics depend on the API. The scenario explicitly asks for complete PUT-style replacement.

C:

GET requests a representation and is not the documented replacement operation. A request body does not turn a safe read into a PUT write.

D:

OPTIONS may discover supported communication options; it does not perform replacement of network configuration. The API documents PUT for this operation.

Question 580

A RESTCONF-based provisioning service must create a new supported configuration resource through an API that documents POST creation on the parent collection. Which operation should it choose?

  1. Issue an authenticated POST to the documented parent resource with a valid request body and check the server response.
  2. Use DELETE against the parent to allocate an unused resource identifier.
  3. Use GET to create the child because GET normally writes configuration state.
  4. Use an ICMP echo request instead of HTTP with an API payload.

Explanation

Correct Answer

A:

POST can ask a REST endpoint to create a child resource when that operation is defined by the API. The endpoint may return a created-resource status such as 201 and a resource location. The client must validate schema, permissions and any conflict response rather than assuming creation always succeeds.

Incorrect Answers

B:

DELETE removes a target according to the API contract and is not a resource-creation operation. It could destroy configuration rather than add a child.

C:

GET has safe retrieval semantics and should not be used to create configuration. The question explicitly identifies a POST creation contract.

D:

ICMP echo tests IP reachability; it has no REST resource-creation method or schema. Connectivity verification does not replace a documented POST operation.