[Practice Exams] AWS Certified AI Practitioner-Video(Part-2)

Name: [Practice Exams] AWS Certified AI Practitioner-Video(Part-2)
Rating: 4.6 (30 reviews)

Confidently Pass the AWS Certified AI Practitioner with Step-by-Step Video Explanations for Every Question

Created byPrashant Lakhera

Last updated 9/2024

English

What you'll learn

Master the AWS Certified AI Practitioner (AIF-C01) exam through targeted practice
32 video lectures, each providing an explanation of every question.
Walk through each question step-by-step to solidify your understanding.
Learn not just the answers, but the reasoning behind them for real exam readiness
Video lectures are aligned with the AWS Certified AI Practitioner (AIF-C01) exam structure.
Perfect for reinforcing knowledge and mastering the exam through visual learning.

Course content

2 sections • 33 lectures • 1h 18m total length

NOTE0:17

Quiz2: Practice Exam - AWS Certified AI Practitioner
Question1:Which ML approach fine-tunes a pre-trained model for your data?2:46
Leverage transfer learning to fine-tune a pre-trained model on limited medical image data, boosting accuracy when data is scarce.
Question2: Which feature ensures throughput for fine-tuning?2:39
Question 3: Most flexible Amazon Bedrock pricing model for usage?3:12
On demand pricing offers the most flexibility on Amazon Bedrock, charging only for usage and supporting cross-region inference for text generation, embeddings, and image generation tasks.
Question 4: Best AWS service for AI chatbot with customization?2:56
Question 5: What AWS service logs API calls for compliance needs?2:34
Question 6: Reducing token costs for generative AI, what method?2:17
Question 7: AWS feature to track and manage ML model versions?2:26
Question 8: AWS service for real-time ML model predictions?2:50
Question 9: Service to host large language models in AWS?2:24
Question 10: AWS database service for similarity searches and vectors?2:25
Question 11: AWS tool to convert thousands of PDFs to text files?3:03
Question 12: AWS service to identify celebrities in a large image set?2:25
Question 13: Feature to manage ML model cards and documentation?2:20
Question 14: AWS tool for on-demand security and compliance reports?2:26
Question 15: ML approach for transfer learning with small datasets?2:19
Explore why large language models sometimes produce factually incorrect or fabricated outputs, a phenomenon known as hallucination, and examine the reasoning behind selecting the correct term from options.
Question 16: Amazon OpenSearch use case for AI and semantic search?2:48
Question 17: Benefits of fine-tuning models on specific data tasks?2:37
Question 18: SageMaker tool to automate and monitor ML processes?2:24
Question 19: How to ensure fairness in model predictions on segments?2:11
Question 20: AWS SageMaker feature to catalog and share models?2:35
Question 21: Service for extracting text and images from documents?2:31
Question 22: AWS service for celebrity identification in image datasets?2:21
Question 23: AWS SageMaker tool for quick ML model deployment?2:13
Learn how instruction fine tuning trains a foundation model to understand and follow specific directions, enabling an AI teaching assistant to provide guided, contextually accurate responses.
Question 24: Amazon Bedrock tool for automating multi-step tasks?1:59
Question 25: AWS services for hosting and managing large AI models?2:09
This lecture explains retrieval augmented generation, enabling a large language model to access external knowledge during inference with minimal development effort.
Question 26: Approach to optimize costs for generative AI model usage?2:23
Question 27: AWS feature to enhance model version tracking and usage?2:10
Question 28: AWS database service for embedding vectors and search?2:15
Question 29: Which AWS inference method provides lowest latency?1:43
Question 30: Service to integrate with SageMaker Ground Truth for labels?2:01
Identify the machine learning sequence: data collection, data preprocessing, model training, and model evaluation, and understand how these steps flow toward evaluating model performance with sage maker ground truth labels.
Question 31: Techniques in Amazon Q's Business web application flow?2:14
Question 32: Amazon Q Developer accessibility: IDEs or Console?2:10

Requirements

To take this practice test, you should have a basic understanding of AWS and foundational knowledge of machine learning concepts

Description

Are you preparing for the AWS Certified AI Practitioner (AIF-C01) exam and want to ensure you pass with confidence? This course is designed to help you succeed by providing comprehensive, step-by-step explanations for each question, ensuring you fully understand the core concepts of AI and machine learning within the AWS ecosystem.

With 32 detailed video lectures, this course walks you through practice questions covering a range of topics, including foundational AI concepts, machine learning models, and the use of key AWS services such as Amazon SageMaker and AWS Bedrock. Each video breaks down complex questions, helping you grasp not just the answers, but the underlying reasoning and logic, so you’ll be fully prepared for the exam.

This course is perfect for those with basic knowledge of AWS and machine learning, and it is ideal for anyone looking to pass the AWS Certified AI Practitioner exam on their first attempt. The practice exams and detailed explanations provide the perfect combination of knowledge and exam readiness, equipping you with everything you need to succeed.

Enroll today and start your journey toward becoming a certified AWS AI Practitioner and clear AWS AI Practitioner exam with confidence!

If you come across any question that seems incorrect, please don't hesitate to send me your feedback. I'd appreciate your input!"

Who this course is for:

This course is for anyone aiming to pass the AWS Certified AI Practitioner (AIF-C01) exam with confidence by gaining a solid understanding of the core concepts.

[Practice Exams] AWS Certified AI Practitioner-Video(Part-2)

What you'll learn

Explore related topics

Course content

NOTE1 lecture • 1min

Introduction32 lectures • 1hr 18min

Requirements

Description

Who this course is for: