Udemy - Aws Certified Ai Practitioner Updated

Free Download Udemy – Aws Certified Ai Practitioner Updated
Published 11/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.66 GB | Duration: 8h 46m
Master AI on AWS: From Basics to Certification – Build, Train & Deploy ML Models with Real-World Applications.

What you’ll learn
Foundations of AI and Machine Learning
AWS AI Services
Machine Learning Lifecycle on AWS
Real-World Application of AI
Exam Preparation
End-to-End Model Deployment
Requirements
Basic Understanding of Cloud Computing
Interest in AI and Machine Learning
Basic Technical Skills
Access to an AWS Account
Willingness to Learn
Description
Discover the Power of AI with the AWS Certified AI Practitioner CourseAre you curious about how Artificial Intelligence (AI) can transform industries, accelerate innovation, and reshape the future? Imagine being able to navigate this rapidly growing field with confidence, leveraging the power of AWS to build and deploy intelligent solutions. Whether you’re an aspiring AI practitioner, an IT professional, or simply someone excited about the future of technology, the AWS Certified AI Practitioner course is designed to empower you with the skills and knowledge to become a proficient AI practitioner.Meet Sarah: A Real-Life Example of TransformationSarah, a software engineer from a small company, felt left behind as her colleagues moved into roles focused on AI and machine learning. She felt the industry was moving forward without her, yet she didn’t know where to start. All she needed was the right guidance and tools to unlock her potential. That’s when she enrolled in our AWS Certified AI Practitioner course, and in just a few weeks, Sarah went from uncertainty to confidence. She was soon leading her own projects, applying the AI skills she’d learned, and experiencing growth she once only dreamed of.Imagine yourself in Sarah’s shoes – your story could be next.Why AI is Essential ?AI is more than just a buzzword. It’s a transformative force across sectors, from healthcare and finance to retail and logistics. Companies around the globe are increasingly integrating AI into their strategies to drive automation, streamline operations, and enhance customer experience. However, there’s a shortage of skilled AI practitioners who understand the technology, tools, and real-world applications of AI. AWS offers a robust platform for building, training, and deploying AI models, and by becoming an AWS Certified AI Practitioner, you position yourself as a critical asset in this evolving landscape.What Makes This Course DifferentThe AWS Certified AI Practitioner course is your pathway to mastering AI on the world’s most widely adopted cloud platform. Unlike other courses that overwhelm you with complex math and coding, this course is designed with a practical, accessible approach. You don’t need a background in AI or machine learning to succeed here – just a curiosity and willingness to learn. Our structured modules break down complex concepts into digestible, actionable steps. The curriculum, crafted by industry experts, prepares you not only to pass the AWS Certified AI Practitioner exam but also to apply your skills in real-world scenarios.The Journey to Certification: Your Path to Becoming an AI PractitionerThe AWS Certified AI Practitioner course is divided into structured modules that gradually build your understanding, from foundational concepts to advanced applications:Introduction to AI and Machine LearningBegin with a clear understanding of what AI and machine learning are and why they matter. Discover how AWS is driving innovation in AI and explore real-world case studies that bring concepts to life. You’ll learn about the broader landscape of AI, including supervised and unsupervised learning, and understand where AWS services like SageMaker and Rekognition fit in.Building Blocks of AI on AWSDive into AWS’s comprehensive suite of AI services. From language processing to computer vision and data analysis, this module covers the essential tools available on AWS. Understand how to use Amazon SageMaker for building and training machine learning models, Amazon Polly for text-to-speech, and Amazon Rekognition for image recognition. You’ll see how these services simplify the development of AI applications without requiring deep technical expertise.Developing AI Skills with Real-World ApplicationsTheory is great, but application is where the real learning happens. This module walks you through hands-on projects that show you how to apply your skills in various scenarios, from building chatbots with Amazon Lex to creating personalized recommendations with machine learning algorithms. By the end of this module, you’ll have real-world experience and projects you can add to your portfolio.Machine Learning Lifecycle on AWSGain a comprehensive understanding of the machine learning lifecycle. You’ll learn about data collection, data preprocessing, model training, tuning, and deployment. See how AWS services can be used throughout each phase, making it possible to build end-to-end machine learning pipelines. This module is designed to give you a strong grasp of how to build production-ready AI systems.What You Will AchieveBy the end of this course, you will:Understand core concepts in AI and machine learning and how to apply them in real-world scenarios.Be proficient in using AWS AI tools and services, including Amazon SageMaker, Rekognition, Polly, and Lex.Be fully prepared to pass the AWS Certified AI Practitioner exam, showcasing your skills to employers.Meet Your Instructors: Experts Who Understand Your JourneyOur instructors are AWS-certified AI practitioners with years of experience in the industry. They know the challenges you face and the skills you need to succeed. The curriculum is built from their firsthand experience, with a focus on practical skills that are immediately applicable in real-world settings. You’re not just learning from instructors; you’re learning from mentors who are committed to your success.Why Certification MattersEarning the AWS Certified AI Practitioner certification opens doors to new career opportunities and higher earning potential. It demonstrates to employers that you possess a strong understanding of AI and machine learning principles and that you can apply this knowledge on the AWS platform. This certification is recognized worldwide, providing you with a competitive edge in the job market and positioning you as a leader in AI.A Certification That Pays OffSarah’s story is just one example of how the AWS Certified AI Practitioner course can transform lives. Since completing the course and passing the exam, she has landed a role as an AI consultant, helping companies integrate AI solutions into their operations. She has more confidence, higher earning potential, and a skill set that’s in demand. Like Sarah, you too can unlock these opportunities.Join Us and Take the First Step Toward Your AI JourneyThe AWS Certified AI Practitioner course is more than just a course; it’s an investment in your future. By gaining the skills to harness the power of AI on AWS, you’re positioning yourself as a leader in one of the most exciting fields in tech today. Don’t let this opportunity pass you by – join us and become part of a community that’s shaping the future with AI.Enroll today and turn your curiosity about AI into a powerful skill set that will propel your career forward.
Overview
Section 1: Introduction
Lecture 1 Orientation
Section 2: Fundamentals of AI and Machine Learning
Lecture 2 Introduction to Domain 1
Lecture 3 Understanding Key Terms
Lecture 4 Instructor Appreciation
Lecture 5 Difference Between AI vs ML vs Deep Learning
Lecture 6 Types of Data
Lecture 7 Types of Machine Learning
Lecture 8 Quick Review on the Progress
Lecture 9 Classification Algorithms
Lecture 10 Evaluation of Classificaiton Algorithms
Lecture 11 Confusion Matrix
Lecture 12 Applications of Confusion Matrix
Lecture 13 Typical Questions in the Examination
Lecture 14 AWS AI Services – Transcribe – Translate – Lex – Polly – Questions Discussion
Lecture 15 Understanding Regresison Models
Lecture 16 Evaluation of Regression Models
Lecture 17 Data Processing in Machine Learning
Lecture 18 Cross Validation in Machine Learning
Lecture 19 Hyperparameter Tuning in Machine Learning
Lecture 20 Unsupervised machine Learning
Lecture 21 Quick Summary
Lecture 22 Types of Unsupervised Learning
Lecture 23 Introduction to Deep Learning
Lecture 24 Convolutional Neural Networks
Lecture 25 Inferencing – Batch Vs Realtime
Lecture 26 Domain 1 Conclusion
Section 3: Amazon Bedrock and Generative AI
Lecture 27 Introduction to Domain 2
Lecture 28 How we proceed in this Section
Lecture 29 Introduction to Generative AI
Lecture 30 Understanding Foundation Models
Lecture 31 Understanding LLM
Lecture 32 Amazon Bedrock
Lecture 33 Amazon Bedrock – Key Features & Benefits
Lecture 34 Amazon Bedrock – Labs
Lecture 35 Amazon Bedrock – inference Parameters & Bedrock Playground
Lecture 36 Quick idea on Cost settings
Lecture 37 Amazon Bedrock Providers & Models
Lecture 38 Exploring the Features of Amazon Bedrock
Lecture 39 Quick Check-in with Instructor
Lecture 40 Prompt Management
Lecture 41 Understanding Knowledgebase and RAG
Lecture 42 Intuition of Embedding Model & Knowledge Store
Lecture 43 RAG Vector Databases , Data Sources & Applications
Lecture 44 Amazon Bedrock Agents & Prompt Flows
Lecture 45 Amazon Bedrock Inference
Lecture 46 Amazon Bedrock Safeguards
Lecture 47 Amazon Bedrock Configurations – Pricing – Security – Deep Dive
Lecture 48 Amazon Bedrock – IAM & Quick Review of Syllabus
Section 4: Prompt Engineering
Lecture 49 Architecture of a Prompt
Lecture 50 Types of Prompt Engineering Techniques
Lecture 51 Data Augmentation for LLMs
Lecture 52 Reinforcement Learning with Human Feedback (RLHF) and LoRA
Lecture 53 A/B Testing in LLMs
Lecture 54 Evaluation of LLMs & RAG Applications
Lecture 55 Inference Optimization for Large Language Models
Lecture 56 Zero Shot Testing and Benchmark Tests
Lecture 57 Hallucination in LLMs
Section 5: Amazon Bedrock – Foundation Models Deep Dive
Lecture 58 Sagemaker – MLOps – Domain 1 to 3 Quick Review and Learn
Section 6: Responsible AI
Lecture 59 Amazon Q
Lecture 60 Amazon Q pricing and Amazon PartyRock
Lecture 61 Services for Responsible AI
Section 7: Security, Compliance and Governance of AI Systems
Lecture 62 Security, Compliance and Governance
Aspiring AI Practitioners,IT and Cloud Professionals,Data Analysts and Business Intelligence Professionals,Developers and Software Engineers,Business and Product Managers in Tech,Students and Career Changers,Certified AWS Professionals
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