Master AWS Generative AI & Ace AI Certification (2024)
Focused View
7:30:59
1 -Introduction.mp4
03:56
1 -AI Fundamentals.mp4
06:15
1 -Module 1 - AI ML Fundamentals.pdf
2 -Making a recommendation.mp4
06:19
3 -What is a Model.mp4
06:55
4 -Model - An Analogy.mp4
07:56
5 -Supervised, Unsupervised and Reinforcement.mp4
17:08
6 -Comparison.mp4
03:54
7 -Data Types.mp4
02:54
8 -Batch and Real-time Inference.mp4
03:40
9 -Deep Learning.mp4
09:06
1 -Module 2 - Generative AI Fundamentals.pdf
1 -What is Generative AI.mp4
02:35
2 -Foundation Models.mp4
11:15
3 -Large Language Model (LLM).mp4
03:34
4 -Transformer Models.mp4
08:14
5 -Text Generation.mp4
07:07
1 -Gen AI at AWS.mp4
09:00
1 -Module 3 - Generative AI at AWS.pdf
2 -Amazon Bedrock.mp4
08:44
3 -Amazon Bedrock - Demo.mp4
08:31
4 -Amazon Bedrock - Terminologies.mp4
07:05
5 -Customization.mp4
04:53
6 -Prompt Engineering.mp4
14:58
7 -Retrieval Augmented Generation (RAG).mp4
06:59
8 -Knowledge Bases.mp4
10:15
9 -Amazon Bedrock Agents - Part 1.mp4
10:42
10 -Amazon Bedrock Agents - Part 2.mp4
11:35
11 -Pricing.mp4
06:34
12 -Integration with other services.mp4
06:24
13 -Guardrails.mp4
10:30
14 -Randomness and diversity.mp4
05:53
1 -Fine Tuning.mp4
05:49
1 -Module 4 - Finetuning your model.pdf
2 -Fine-tuning vs. Continued Pre-training.mp4
06:58
3 -Custom Model in Amazon Bedrock.mp4
15:41
1 -Module 5 - Build your own model.pdf
1 -Why build your own model.mp4
02:16
2 -Analogy - Beer or Wine Prediction Model.mp4
11:51
3 -Roles in ML Team.mp4
04:29
4 -MLOps.mp4
07:25
5 -Amazon SageMaker.mp4
07:01
6 -Components and Features.mp4
02:01
7 -Prepare your data.mp4
17:47
8 -Build your model.mp4
09:27
9 -Train your model.mp4
03:36
10 -Deploy your model.mp4
04:21
11 -Amazon SageMaker Endpoints.mp4
10:11
12 -End-to-End-Demo-Part 1.mp4
19:09
13 -End-to-End-Demo-Part 2.mp4
11:57
1 -Module 6 - Monitor your model.pdf
1 -Monitoring Business Metrics.mp4
04:25
2 -Monitoring Technical Metrics.mp4
11:02
1 -Module 7 - Responsible AI.pdf
1 -Responsible AI.mp4
05:13
2 -Tackle AI Challenges.mp4
09:40
1 -AWS AI ML Stack.mp4
04:13
1 -Module 8 - ML services in AWS.pdf
2 -Amazon Augmented AI.mp4
03:48
3 -Amazon Comprehend.mp4
04:27
4 -Amazon Fraud Detector.mp4
02:47
5 -Amazon Kendra.mp4
03:37
6 -Amazon Lex.mp4
02:10
7 -Amazon Personalize.mp4
04:34
8 -Amazon Polly.mp4
02:57
9 -Amazon Q Business and Developer.mp4
04:59
10 -Amazon Rekognition.mp4
02:57
11 -Amazon Textract.mp4
03:16
12 -Amazon Transcribe.mp4
03:32
13 -Amazon Translate.mp4
03:06
14 -Other AWS Services.mp4
04:32
1 -Getting ready for exam.mp4
06:54
1 -Module 9 - Get Ready for Exam.pdf
More details
Course Overview
This comprehensive course teaches Generative AI concepts and AWS implementation, preparing you to confidently pass the AWS AI Practitioner Certification (AIF-C01) with hands-on learning.
What You'll Learn
- Fundamentals of AI/ML and Generative AI technologies
- Practical AWS implementation with Amazon Bedrock and SageMaker
- Responsible AI practices and certification exam strategies
Who This Is For
- Aspiring AI practitioners with no coding experience needed
- Professionals preparing for AWS AI certification
- Anyone wanting to learn Generative AI through practical examples
Key Benefits
- Zero to certification-ready in one course
- Hands-on with AWS AI services like Bedrock and SageMaker
- Learn through easy analogies and real-world applications
Curriculum Highlights
- AI/ML and Generative AI fundamentals
- AWS implementation with Bedrock and SageMaker
- Responsible AI and certification preparation
Focused display
Category
- language english
- Training sessions 64
- duration 7:30:59
- Release Date 2025/04/26
