Learn Generative Ai And Pass Aws Ai Certification
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.04 GB | Duration: 7h 31m
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.04 GB | Duration: 7h 31m
Learn and effectively demonstrate overall knowledge of AI/ML, generative AI technologies - Reach out for discount coupon
What you'll learn
Understand AI, ML, and generative AI concepts, methods, and strategies in general and on AWS.
Understand the appropriate use of AI/ML and generative AI technologies to ask relevant questions within the candidate’s organization.
Determine the correct types of AI/ML technologies to apply to specific use cases.
Use AI, ML, and generative AI technologies responsibly.
Acquire the knowledge and pass AWS AI Practitioner Exam (AIF-C01) with confidence
Requirements
No programming or machine learning experience needed
Description
Whether you’re new to generative AI or an experienced builder, develop your knowledge and skills with training curated by an experts AWS authorized professional. This course will help you to develop a holistic understanding of generative AI to keep pace with advancements and form business insights.Generative artificial intelligence (generative AI) is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. AI technologies attempt to mimic human intelligence in non-traditional computing tasks like image recognition, natural language processing (NLP), and translation. Generative AI is the next step in artificial intelligence.You’ve probably heard a lot of conversation about artificial intelligence (AI) and generative AI. According to a study by AWS, hiring AI-skilled talent is a priority among 73% of employers—but three out of four who consider it a priority can’t find the AI talent they need.And AI skills aren’t just for techies; having a grasp of cloud and AI fundamentals can help you future-proof careers in business roles, such as marketing, program management, and customer support. Showcasing your understanding of AI concepts can give you an edge in the global job market. According to AWS’s study, organizations are willing to pay a premium for professionals with AI skills. This includes salaries that are up to 47% higher for IT workers, 43% higher for those in sales and marketing, and 42% higher for those in finance.Recognizing the value of AI in all industries, AWS recently launched a new certification to empower professionals with the knowledge to drive AI adoption responsibly. The new AWS Certified AI Practitioner certification could be the perfect credential to help launch – or advance – your tech career, and sharpen your competitive edge in business careers. This certification validates your understanding of core AI and machine learning (ML) concepts and use cases, as well as your ability to identify appropriate AWS services to implement AI solutions.Are you ready to take a streamlined approach to getting ahead of the competition in today’s global workforce? I am excited to announce a new learning pathway to help learners prepare for this certification exam.You would learn about the following exam domains:• Domain 1: Fundamentals of AI and ML (20% of scored content)• Domain 2: Fundamentals of Generative AI (24% of scored content)• Domain 3: Applications of Foundation Models (28% of scored content)• Domain 4: Guidelines for Responsible AI (14% of scored content)• Domain 5: Security, Compliance, and Governance for AI Solutions (14% of scored content)
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: AI ML Fundamentals
Lecture 2 AI Fundamentals
Lecture 3 Making a recommendation
Lecture 4 What is a Model?
Lecture 5 Model - An Analogy
Lecture 6 Supervised, Unsupervised and Reinforcement
Lecture 7 Comparison
Lecture 8 Data Types
Lecture 9 Batch and Real-time Inference
Lecture 10 Deep Learning
Section 3: Generative AI Fundamentals
Lecture 11 What is Generative AI?
Lecture 12 Foundation Models
Lecture 13 Large Language Model (LLM)
Lecture 14 Transformer Models
Lecture 15 Text Generation
Section 4: Generative AI at AWS
Lecture 16 Gen AI at AWS
Lecture 17 Amazon Bedrock
Lecture 18 Amazon Bedrock - Demo
Lecture 19 Amazon Bedrock - Terminologies
Lecture 20 Customization
Lecture 21 Prompt Engineering
Lecture 22 Retrieval Augmented Generation (RAG)
Lecture 23 Knowledge Bases
Lecture 24 Amazon Bedrock Agents - Part 1
Lecture 25 Amazon Bedrock Agents - Part 2
Lecture 26 Pricing
Lecture 27 Integration with other services
Lecture 28 Guardrails
Lecture 29 Randomness and diversity
Section 5: Finetuning your model
Lecture 30 Fine Tuning
Lecture 31 Fine-tuning vs. Continued Pre-training
Lecture 32 Custom Model in Amazon Bedrock
Section 6: Build your own model
Lecture 33 Why build your own model?
Lecture 34 Analogy - Beer or Wine Prediction Model
Lecture 35 Roles in ML Team
Lecture 36 MLOps
Lecture 37 Amazon SageMaker
Lecture 38 Components and Features
Lecture 39 Prepare your data
Lecture 40 Build your model
Lecture 41 Train your model
Lecture 42 Deploy your model
Lecture 43 Amazon SageMaker Endpoints
Lecture 44 End-to-End-Demo-Part 1
Lecture 45 End-to-End-Demo-Part 2
Section 7: Monitoring your model
Lecture 46 Monitoring Business Metrics
Lecture 47 Monitoring Technical Metrics
Section 8: Responsible AI
Lecture 48 Responsible AI
Lecture 49 Tackle AI Challenges
Section 9: AWS AI ML Services
Lecture 50 AWS AI ML Stack
Lecture 51 Amazon Augmented AI
Lecture 52 Amazon Comprehend
Lecture 53 Amazon Fraud Detector
Lecture 54 Amazon Kendra
Lecture 55 Amazon Lex
Lecture 56 Amazon Personalize
Lecture 57 Amazon Polly
Lecture 58 Amazon Q Business and Developer
Lecture 59 Amazon Rekognition
Lecture 60 Amazon Textract
Lecture 61 Amazon Transcribe
Lecture 62 Amazon Translate
Lecture 63 Other AWS Services
Section 10: Getting ready for exam
Lecture 64 Getting ready for exam
Anyone who wants to learn about Generative AI in easy and fun way through analogies,Anyone who is preparing for AWS AI Practitioner Certification