AIF-C01 AWS Certified AI Practitioner Ultimate Course 2025

Welcome to the ultimate guide for the AIF C01 AWS Certified AI Practitioner course! In this video, we dive deep into everything you need to ace the certification exam.

What You'll Learn:

1. In-Depth Hands-On Projects: Implement end-to-end architecture diagrams and gain practical experience.

2. How to upload a .wav audio file from your local computer to an Amazon S3 bucket.

3. How to create a transcription job using Amazon Transcribe to extract text from the audio file.

4. How to review and validate the transcription results.

5. Theory Concepts: Understand the core principles and theoretical foundations of AI on AWS.

6. Practice Test Questions: Tackle exam-style questions with detailed explanations for each correct and incorrect answer, using the method of elimination.

Steps Covered:

1. Sign in to AWS Management Console: We'll start by signing in to the AWS Management Console and setting the default region to US East (N. Virginia).

2. Create an S3 Bucket: Learn how to create an S3 bucket to store your audio file.

3. Upload Audio File: We'll show you how to upload a .wav audio file from your local computer to the S3 bucket.

4. Create Transcription Job: Discover how to create a transcription job in Amazon Transcribe and select the uploaded audio file for transcription.

5. Review Transcription Results: Finally, we'll review the transcription results and show you how to access the transcribed text.

Welcome to our in-depth tutorial on Analyzing Text Insights Using Amazon Comprehend! In this video, we'll guide you through the process of leveraging Amazon Comprehends real-time analysis capabilities to extract valuable insights from text.

What You'll Learn:

1. Entities Extraction: Identify and categorize entities such as people, places, brands, and events from your text.

2. Key-Phrases Detection: Extract key phrases to understand the main topics and themes.

3. Language Identification: Automatically detect the language of the input text.

4. PII Detection: Identify and protect personally identifiable information (PII) within your text.

5. Sentiment Analysis: Determine the overall sentiment (positive, negative, neutral, or mixed) of the text.

Steps Covered:

1. Introduction to Amazon Comprehend: Overview of the service and its capabilities.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon Comprehend.

3. Uploading Input Text: Steps to upload your text data for analysis.

4. Real-Time Analysis: Perform real-time analysis to extract entities, key phrases, language, PII, and sentiment.

5. Reviewing Results: How to interpret and utilize the insights provided by Amazon Comprehend.

Welcome to our comprehensive tutorial on Real-Time Translation Using Amazon Translate In this video, we'll guide you through the process of translating text from Spanish to English in real-time using the AWS console. Additionally, we'll demonstrate how to upload a Dutch text file and translate it to English using the Document tab.

What You'll Learn:

1. Real-Time Translation: Translate text from Spanish to English instantly using Amazon Translate.

2. Document Translation: Upload a Dutch text file from local computer and translate it to English using the Document tab in Amazon Translate.

3. AWS Console Navigation: Learn to navigate the AWS console to access Amazon Translate.

4. Step-by-Step Instructions: Follow detailed steps to perform translations and review the results.

Steps Covered:

1. Introduction to Amazon Translate: Overview of the service and its capabilities.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon Translate.

3. Real-Time Translation: Enter Spanish text in the AWS console and translate it to English in real-time.

4. Uploading Dutch Text File: Steps to upload a Dutch text file suing Document Tab in Amazon Translate.

5. Document Translation: Use the Document tab in Amazon Translate to translate the uploaded Dutch text file to English.

6. Reviewing Results: How to interpret and utilize the translated text.

Welcome to our hands-on project tutorial on Redacting PII Data Using Amazon Transcribe In this video, we'll guide you through an end-to-end project designed for restaurant businesses that accept orders via phone calls. Learn how to use Amazon Transcribe to redact sensitive customer information such as names, phone numbers, and addresses from recorded audio files.

What You'll Learn:

1. Recording Orders: How to record customer orders via phone calls and save them as .wav files.

2. Uploading to S3: Steps to upload the recorded .wav files to an Amazon S3 bucket.

3. Creating Transcription Jobs: How to create transcription jobs using Amazon Transcribe to extract text from the audio files.

4. Redacting PII Data: Techniques to automatically redact personally identifiable information (PII) from the transcriptions.

5. Forwarding to Chef: How to forward the redacted transcription to the chef for preparing the dishes while ensuring customer privacy.

Steps Covered:

1. Introduction to Amazon Transcribe: Overview of the service and its capabilities.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon Transcribe.

3. Recording and Uploading Audio Files: Record customer orders and upload the .wav files to an S3 bucket.

4. Creating Transcription Jobs: Create transcription jobs in Amazon Transcribe and select the uploaded audio files for transcription.

5. Redacting PII Data: Use Amazon Transcribe's PII redaction feature to automatically hide sensitive customer information.

6. Reviewing and Forwarding Transcriptions: Review the redacted transcriptions and forward them to the chef for order preparation.

Welcome to our hands-on project tutorial on Building And Creating An Index For Searching Using Amazon Kendra In this video, we'll guide you through an end-to-end project where you'll learn how to leverage Amazon Kendra to create a powerful search index.

What You'll Learn:

1. Introduction to Amazon Kendra: Understand the basics of Amazon Kendra and its capabilities.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon Kendra.

3. Creating an Index: Step-by-step instructions on creating an index in Amazon Kendra.

4. Adding Data Sources: Learn how to add data sources, including uploading a .json file to an S3 bucket.

5. Searching Text: Perform searches using Amazon Kendra to find relevant information in the .json file stored in S3.

Steps Covered:

1. Introduction to Amazon Kendra: Overview of the service and its features.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon Kendra.

3. Creating an Index: Detailed steps to create an index in Amazon Kendra.

4. Uploading .json File to S3: Steps to upload your .json file to an Amazon S3 bucket.

5. Adding Data Sources: How to add the S3 bucket as a data source in Amazon Kendra.

6. Performing Searches: Use Amazon Kendra to search the text within the .json file and retrieve relevant results.

7. Reviewing Results: How to interpret and utilize the search results provided by Amazon Kendra.

Welcome to our hands-on project tutorial on Using Custom Vocabulary And PII Redaction With Amazon Transcribe! In this video, we'll guide you through an end-to-end project where you'll learn how to enhance your transcription jobs with custom vocabulary and protect sensitive information using PII redaction.

What You'll Learn:

1. Custom Vocabulary: How to create and use custom vocabulary in an Amazon Transcribe transcription job to improve accuracy for specific terms.

2. PII Redaction: How to enable PII redaction in an Amazon Transcribe transcription job to automatically hide sensitive information such as names, phone numbers, and addresses.

3. Uploading Audio Files: Steps to upload a .WAV audio file from your local computer to an Amazon S3 bucket.

4. Creating Transcription Jobs: How to create transcription jobs in Amazon Transcribe using the uploaded audio file as the source.

Steps Covered:

1. Introduction to Amazon Transcribe: Overview of the service and its capabilities.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon Transcribe.

3. Uploading .WAV File to S3: Steps to upload your .WAV audio file to an Amazon S3 bucket.

4. Creating Custom Vocabulary: How to create a custom vocabulary list and use it in a transcription job.

5. Transcription Job with Custom Vocabulary: Create a transcription job using the custom vocabulary to improve transcription accuracy.

6. Enabling PII Redaction: How to enable PII redaction in a transcription job to protect sensitive information.

7. Transcription Job with PII Redaction and Custom Vocabulary: Create a transcription job that combines PII redaction with custom vocabulary.

8. Reviewing Results: How to interpret and utilize the transcription results provided by Amazon Transcribe.

Welcome to our comprehensive hands-on project tutorial on Amazon OpenSearch and OpenSearch Dashboard In this video, we'll guide you through an end-to-end project where you'll learn how to create and manage an OpenSearch Service Domain, and explore flight sample datasets using OpenSearch Dashboards.

What You'll Learn:

1. Introduction to Amazon OpenSearch: Understand the basics of Amazon OpenSearch and its capabilities.

2. Creating an OpenSearch Service Domain: Step-by-step instructions on setting up an OpenSearch Service Domain.

3. Uploading Sample Datasets: How to upload flight sample datasets to your OpenSearch domain.

4. Using OpenSearch Dashboards: Explore and visualize data using OpenSearch Dashboards.

5. Data Analysis: Perform data analysis and gain insights from the flight sample datasets.

Steps Covered:

1. Introduction to Amazon OpenSearch: Overview of the service and its features.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon OpenSearch.

3. Creating an OpenSearch Service Domain: Detailed steps to create and configure an OpenSearch Service Domain.

4. Uploading Flight Sample Datasets: Steps to upload flight sample datasets to your OpenSearch domain.

5. Exploring OpenSearch Dashboards: How to use OpenSearch Dashboards to visualize and analyze data.

6. Performing Data Analysis: Techniques to analyze the flight sample datasets and extract valuable insights.

Welcome to our hands-on tutorial on Automatically Detecting PII Data In Amazon S3 Using Amazon Macie! In this video, we'll guide you through the process of setting up Amazon Macie to identify and protect sensitive information in your S3 buckets using End-to-End Architecture Diagram Automation.

What You'll Learn:

1. Introduction to Amazon Macie: Understand the basics of Amazon Macie and its capabilities.

2. Uploading PII Files to S3: Steps to upload files containing PII data to an Amazon S3 bucket.

3. Configuring Amazon Macie: How to configure Amazon Macie to detect PII data and use Custom Data Identifiers with RegEx as per business requirements.

4. Integrating with Amazon EventBridge and SNS: Set up integrations to send email notifications for any PII data findings in S3 buckets.

Steps Covered:

1. Introduction to Amazon Macie: Overview of the service and its features.

2. Setting Up the Environment: How to set up your AWS environment for using Amazon Macie.

3. Uploading PII Files to S3: Steps to upload files containing PII data to an Amazon S3 bucket.

4. Configuring Amazon Macie: Detailed steps to configure Amazon Macie to detect PII data and create Custom Data Identifiers using RegEx.

5. Integrating with Amazon EventBridge: How to integrate Amazon Macie findings with Amazon EventBridge.

6. Setting Up SNS Notifications: Configure Amazon SNS to send email notifications for PII data findings.

7. Reviewing Results: How to interpret and utilize the findings provided by Amazon Macie.