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AWS AI Practitioner Certification Course
AWS AI Practitioner Certification Course
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Instructor-led AWS Certified AI Practitioner Foundational live online Training Schedule
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Why enroll for AWS AI Practitioner Certification Course?
AWS AI Practitioner Certification Training Benefits
According to AWS, companies are seeking AI-skilled employees in various domains and are willing to offer 43% higher salaries in sales and marketing, 42% higher in finance, 41% higher in business operations, and 47% higher in IT domains. This highlights the critical importance of receiving advanced AI training for professionals to stay competitive and position themselves for high-paying jobs.
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Want to become a Generative AI Engineer?
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Want to become a Generative AI Engineer?
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Want to become a Generative AI Engineer?
Why AWS AI Practitioner Certification Course from edureka
Live Interactive Learning
- World-Class Instructors
- Expert-Led Mentoring Sessions
- Instant doubt clearing
Lifetime Access
- Course Access Never Expires
- Free Access to Future Updates
- Unlimited Access to Course Content
24x7 Support
- One-On-One Learning Assistance
- Help Desk Support
- Resolve Doubts in Real-time
Hands-On Project Based Learning
- Industry-Relevant Projects
- Course Demo Dataset & Files
- Quizzes & Assignments
Industry Recognised Certification
- Edureka Training Certificate
- Graded Performance Certificate
- Certificate of Completion
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About your AWS AI Practitioner Certification Course
AWS AI Practitioner Certification Course Skills Covered
AWS AI Practitioner Certification Course Tools Covered
AWS AI Practitioner Certification Course Curriculum
Curriculum Designed by Experts
Exploring Artificial Intelligence on AWS
Topics:
- Introduction to Artificial Intelligence
- Fundamentals of Machine Learning
- Essential Concepts in Generative AI
- Understanding Generative AI
- Applications of Generative AI in Enterprises
- Training Employees in Generative AI Usage
- Techniques in Generative AI
- Advantages of Using AWS for Generative AI Development
- Overview of AWS Infrastructure and Technologies
- AI and Machine Learning Services in AWS
- Introduction to Amazon SageMaker
![skill]( "Hands On Experience")
- Working with SageMaker
- Working with SageMaker
![skill]( "skill you will learn")
- Understanding Machine Learning and AI Concepts
- Comprehend the principles and techniques of generative AI
- Navigate and implement AWS infrastructure and technologies for AI/ML projects
AWS AI and ML Applications: Industry Use Cases
15 Topics
Topics:
- AI applications across industries
- AI-driven business solutions
- Strategies for integrating AI into business processes
- Evaluating limitations and constraints for AI adoption
- Use cases for supervised learning in real-world applications
- Applications and benefits of unsupervised learning techniques
- Leveraging reinforcement learning for autonomous decision-making systems
- Overview of generative AI technologies and their applications
- Generative AI Industry use cases
- Future trends and innovations enabled by generative AI
- Ethical considerations in the development and deployment of generative AI
- Factors to consider when selecting appropriate generative AI models
- Methods for evaluating model performance and accuracy
- Practical guidelines for choosing the right model for specific tasks
- Evaluating the impact of generative AI on business outcomes
![skill]( "Hands On Experience")
- AI Applications Across Industries
- AI-Driven Business Solutions
- Strategies for Integrating AI into Business Processes
- AI, ML, and Generative AI Use Cases
![skill]( "skill you will learn")
- Practical AI Applications
- Industry-Specific AI Solutions
- Generative AI Techniques
Machine Learning and Generative AI with AWS
18 Topics
Topics:
- Machine Learning Lifecycle Management
- Developing Machine Learning Solutions with Amazon SageMaker
- Sources for Machine Learning Models
- Evaluating the Performance of Machine Learning Models
- Deploying Machine Learning Models
- Essentials of MLOps
- Lifecycle of Generative AI Applications
- Addressing Bias in Generative AI Models
- Introduction to Foundation Models in AWS
- Importance of Foundation Models
- Operational Mechanisms of Foundation Models
- Types of Foundation Models
- Design Considerations for Foundation Models
- Selecting an Appropriate Foundation Model
- Enhancing Foundation Model Performance
- Evaluating Foundation Models
- Developing Applications with Generative AI Foundation Models in AWS
- Deploying Applications in AWS
![skill]( "Hands On Experience")
- Building and Deploying ML Models with Amazon SageMaker
- Evaluating ML Model Performance
- Exploring Generative AI Foundation Models
- Developing and Deploying Applications with Generative AI
![skill]( "skill you will learn")
- Model Development and Deployment
- Build and deploy generative AI applications
Generative AI with Amazon Bedrock and Amazon Q
10 Topics
Topics:
- Amazon Bedrock Essentials
- Amazon Bedrock Features
- Working with Bedrock API
- Building Generative AI Applications with Bedrock
- Introduction to Amazon Q
- Amazon Q Developer Basics
- Amazon Q Architecture
- Amazon Q Developer features
- Working with Amazon Q Business
- Generative BI with Amazon Q and Quicksight
![skill]( "Hands On Experience")
- Building Generative AI Applications with Bedrock
- Working with Amazon Q
- Understanding Generative BI with Q and Quicksight
![skill]( "skill you will learn")
- Building Applications with Bedrock
- Leveraging Amazon Q
- Generative BI with Q and Quicksight
Prompt Engineering for Generative AI Applications
10 Topics
Topics:
- Understanding Prompts and Their Components
- Techniques for Modifying Prompts
- Parameters for Inference in Prompting
- Best Practices in Prompting
- Engineering Techniques for Effective Prompts
- Zero-shot, Few-shot, and Chain-of-thought Prompting
- Risks and Misuses of Prompts
- Poisoning, hijacking, and prompt injection
- Exposure and prompt leaking
- Jailbreaking
![skill]( "Hands On Experience")
- Designing and Modifying Prompts
- Applying Prompt Engineering Techniques
- Optimizing Inference Parameters
- Identifying and Mitigating Prompt Misuses and Risks
![skill]( "skill you will learn")
- Effective Prompt Design
- Prompt Engineering Techniques
- Risk Management in Prompt Engineering
Optimizing Foundation Models with RAG and Fine-Tuning
8 Topics
Topics:
- Enhancing Foundation Models with Retrieval-Augmented Generation
- Developing a Business Case
- Introduction to Retrieval-Augmented Generation (RAG)
- Utilizing Agents in RAG
- Assessing and Analyzing Results
- Improving Foundation Models through Fine-Tuning
- Applying Fine-Tuning Techniques
- Evaluating Model Performance
![skill]( "Hands On Experience")
- Implementing Retrieval-Augmented Generation (RAG)
- Optimizing Foundation Models with Fine-Tuning
- Evaluating Model Performance
![skill]( "skill you will learn")
- Implementing and Evaluating RAG
- Fine-Tuning Foundation Model
- Model Optimization Techniques
Advanced AWS Services for AI Application Development
11 Topics
Topics:
- Utilizing Amazon Comprehend
- Reviewing Documents in Amazon S3
- Developing Custom Classification Models
- Conducting Real-Time Data Analysis
- Applying Custom Classification Models
- Deploying Large Language Models (LLMs)
- Integrating Amazon Kendra Data Sources
- Building Amazon Lex V2 Chatbots
- Querying Large Language Model Endpoints
- Implementing Retrieval-Augmented Generation (RAG) Workflows
- Deploying Web Applications with AWS CloudFormation
![skill]( "Hands On Experience")
- Reviewing Documents in S3 Buckets
- Creating and Using Custom Classification Models
- Deploying Large Language Models
- Integrating Amazon Kendra and Lex V2
- Querying and Implementing RAG Workflows
- Deploying Web Apps with CloudFormation
![skill]( "skill you will learn")
- Working with Amazon Comprehend
- AI and Chatbot Development with Amazon Kendra and Lex V2
- Advanced Model Querying and RAG Workflows
- Deployment with AWS CloudFormation
Security Compliance and Governance with AWS
8 Topics
Topics:
- AI System Compliance Standards
- AWS Governance and Compliance Services
- Data Governance Strategies
- Implementing Governance Approaches
- Security and Privacy in AI Systems
- AWS Security Features for AI
- Data and Model Lineage
- Best Practices for Secure Data Engineering
![skill]( "Hands On Experience")
- Implementing Data Governance and Compliance
- Securing AI Systems
![skill]( "skill you will learn")
- Governance and Compliance in AI Systems
- AI Security and Policy
Responsible AI Practices and Principles (Self-paced)
9 Topics
Topics:
- Understanding Responsible AI
- Challenges in Implementing Responsible AI
- Key Dimensions of Responsible AI
- Amazon Tools and Services for Responsible AI
- Considerations for Ethical Model Selection
- Ethical Preparation of Datasets
- Transparent and Explainable Models
- Trade-offs in Responsible AI Models
- Human-Centered Design Principles for Explainable AI
![skill]( "Hands On Experience")
- Applying Amazon Services for Responsible AI
![skill]( "skill you will learn")
- Responsible AI Implementation
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About your AWS AI Practitioner Certification Course
What are the objectives of our AWS AI Practitioner Online Training?
Our AWS AI Practitioner Online Training aims to fully prepare you for the AWS Machine Learning - Associate (AIF-C01) test. During training, you will:
- Recognize the fundamental ideas and terms used in machine learning (ML), generative AI, and artificial intelligence (AI).
- Examine practical uses for generative AI, AI, and ML technologies that can spur innovation and address business issues.
- Discover the design considerations and architectural ideas that go into creating strong foundation models for AI applications.
- Learn the methods and strategies for fine-tuning machine learning models to get the performance you want.
- Gain expertise in creating efficient questions and prompts that use generative AI models to produce targeted results.
- Recognize the measures and standards used to assess the efficacy, fairness, and success of foundation models.
- Learn about best practices and ethical issues for creating and using AI systems in a responsible manner.
- Discover the safety and integrity of AI apps and data by learning about the necessary compliance standards and security procedures.
By the end of this course, you will be well-prepared to pass the AWS AWS AI Practitioner Foundational (AIF-C01) exam, having gained practical skills and knowledge that are relevant to the exam topics, ensuring readiness for real-world AWS artificial intelligence scenarios.
What are the prerequisites for Edureka's AWS AI Practitioner Certification Training?
There are no prerequisites for this course. However, participants will benefit from basic knowledge of Python programming, cloud computing, AWS fundamentals, and working knowledge of artificial intelligence.
What is the syllabus of the AWS AI Practitioner Certification Course?
We will cover the following topics to help you prepare for the AWS Machine Learning Engineer Associate (MLA - C01) examination and gain an overall understanding of the AI, ML, and Generative AI lifecycle and its implementation on AWS. The exam will cover the following topics:
- Fundamental concepts and terminologies of AI, ML, and generative AI
- Use cases of AI, ML and generative AI
- Design considerations for foundation models
- Model Training and fine tuning
- Prompt engineering
- Foundation model evaluation criteria
- Responsible AI
- Security and compliance for AI systems
Do I need coding knowledge to take up this program?
No, you do not need to have any prior coding experience to enroll in this course. We will provide the required materials as prerequisites so that you can begin your preparation before the live class starts. However, any prior coding experience will be an added advantage for the participants.
What is the duration of the AWS AI Practitioner Certification Course?
The duration of the AWS AWS AI Practitioner Certification Course is 24 hours.
What are the advantages of learning the AWS Certification Course from Edureka?
The AWS AWS AI Practitioner Foundational Course by Edureka helps you prepare for the certification exam (AIF-C01) and become a certified AI practitioner. You will have advantages like:
- Access to instructor-led live sessions
- Professional Community forum
- 24/7 expert support
- Pre-requisite learning materials
- Lifetime access to LMS, where presentations, quizzes, installation guides & class recordings are available
What are the system requirements for this AWS AI Practitioner Certification Course?
The system requirements to attend this AWS AI Practitioner Foundational Certification Course Online include a minimum of 8 GB RAM, an Intel Core i3 processor or above, 20 GB HDD, and a stable internet connection.
How will I execute practicals in this AWS AWS AI Practitioner Certification Course?
In this course, you will work on Amazon's cloud servers and other services. You can create a Free Tier account on AWS, giving you access to all the AWS services. The stepwise guide for accessing these services will be available in the LMS, and Edureka’s support team will assist you 24/7 if you have any doubts.
About your AWS AI Practitioner Certification Course Project
Enhanced Product Design using Generative AI on AWS
Designing products that match consumer aspirations for innovation and personalization while optimizing design processes is still a problem. Traditional design methodologies are g....Email Spam Classification using Machine Learning on AWS
Email spam is an enormous issue, affecting user productivity and email security. Traditional rule-based email filtering solutions frequently fail to effectively distinguish betwe....AWS AI Practitioner Certification Course Details
To unlock Edureka’s AWS AI Practitioner Certification Course completion certificate, you must ensure the following:
- Completely participate in Edureka’s AWS AI Practitioner Certification Course.
- Complete the quizzes and projects listed.
Cloud computing is in huge demand in the industry, and the latest studies suggest that the cloud computing market will continue to grow in the coming years. Various companies are switching from using their own data centers to third-party cloud service providers. Consequently, businesses have been able to reduce costs and improve service significantly. There will be a need for a workforce in the industry as the sector appears to grow considerably in the future.
Due to the rapid growth of artificial intelligence (AI) and its widespread use across various sectors, it offers promising career opportunities. The demand for skilled professionals in areas such as computer vision, natural language processing, and machine learning will increase as AI technologies advance. AI professions can offer significant financial rewards and make a meaningful difference in a range of sectors such as technology, healthcare, and finance. In order to thrive in this rapidly evolving field, budding AI professionals need to stay current with advancements in technology and acquire essential skills through training and hands-on experience.
Amazon Web Services (AWS) is Amazon's cloud computing platform. It provides several services, including computing, storage, networking, databases, artificial intelligence, machine learning, analytics, security, and more. AWS enables businesses to build and deploy applications and services with greater scalability and reliability compared to traditional on-premises infrastructure.
AWS is a user-friendly and popular cloud computing service that beginners can easily familiarize themselves with. Proper guidance and a well-structured training course are necessary to learn its services and functionality. Beginners aspiring to pursue a career in AWS can sign up for our training courses and earn certificates to demonstrate their expertise in this domain.
AWS certifications significantly boost your cloud computing knowledge and your ability to command a higher wage. AWS AI Practitioner Certification validates your skills and expertise in leveraging AWS for AI-powered solutions and positions you higher up in order to get Cloud-based AI and Generative AI-related jobs.
Amazon Web Services (AWS) has introduced multiple certifications across domains for professionals who want to upskill themselves as per their preferred learning path. These certificates are designed for professionals with different levels of experience and expertise in various domains, such as:
- Associate: These certifications are role-based and allow aspirants to build their credibility as certified AWS professionals. Prior on-premise or cloud hands-on IT experience is required to clear the certification examination and obtain the certification.
- Professional: These certifications are role-based and allow aspirants to build their credibility as certified AWS professionals. 2 years of AWS cloud experience are required to clear the certification examination and obtain the certification.
- Specialty: These certifications are suitable for professionals who want to specialize in a particular field and position themselves as trusted advisors to their stakeholders and customers in these strategic areas.
The exam duration is 120 minutes.
The exam consists of 85 questions based on the topics outlined by AWS.
The exam costs 75 USD/10,000 JPY. Visit the Exam pricing page for additional cost information, including foreign exchange rates.
Individuals who have working knowledge of AI/ML technologies on AWS but may not actually develop solutions with them.
You can take the exam at a Pearson VUE testing location or online through a proctored exam.
The exam is offered in English and Japanese.
The World Economic Forum's Future of Jobs Report 2023 predicts a 40% increase in demand for AI and Machine Learning Specialists. However, 70% of IT leaders in North America report needing help recruiting qualified AI/ML personnel. Earning this certification can help you land sought-after artificial intelligence jobs in the AWS Cloud environment.
For those transitioning into the cloud industry, we suggest getting the AWS Certified Solutions Architect - Associate credential. We encourage anyone pursuing careers in data, artificial intelligence, and machine learning to consider obtaining certifications such as the AWS Certified Data Engineer - Associate or the AWS Certified Machine Learning Engineer - Associate.
No, we do not provide any exam vouchers for this course.
John Doe
Title
with Grade X
XYZ123431st Jul 2024
The Certificate ID can be verified at www.edureka.co/verify to check the authenticity of this certificate
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AWS AI Practitioner Certification Course
What if I miss the AWS AI Practitioner Certification Course classes?
You will never miss a lecture at Edureka! as you can always view the recorded session of the class available in your LMS.
So, what are you waiting for?
Let’s enroll with Edureka and learn the best AWS AWS AI Practitioner Certification Course online with our top instructors.
Will I get placement assistance after completing this AWS AI Practitioner Certification Course?
To help you in this endeavor, we have added a resume builder tool to your LMS. Now, you will be able to create a winning resume in just three easy steps. You will have unlimited access to these templates across different roles and designations. You just need to log in to your LMS and click on the "create your resume" option.
Who are the instructors for the AWS AI Practitioner Certification Course?
All the instructors at Edureka are industry practitioners with a minimum of 10–12 years of relevant experience. They are subject matter experts trained by Edureka to provide an awesome learning experience to the participants.
What if I have more queries after completing the AWS AI Practitioner Certification Course?
Just give us a call at +91 98702 76459/1844 230 6365 (US Tollfree Number) or email at sales@edureka.co.
What if I miss a class of AWS AI Practitioner Certification Course?
You will never miss a lecture at Edureka! You can choose either of the two options:
- View the recorded class session available in your LMS.
- You can attend the missed session or any other live batch.
What if I have queries after I complete this AWS AI Practitioner Certification Course?
Your access to the Support Team is for a lifetime and will be available 24/7. The team will help you resolve queries during and after the completion of this certification course.
How soon after signing up would I get access to the Learning Content?
Post-enrolment, the LMS access will be instantly provided to you and will be available for a lifetime. You can access the complete set of previous class recordings, PPTs, PDFs, and assignments. Moreover, access to our 24×7 support team will be granted instantly. You can start learning right away.
Will the course material be available to learners after completion of the course?
Yes, once you enroll in the AWS AI Practitioner Certification Course, you will have lifetime access to the course material.
Is this course 100% online? Do I need to attend any physical classes?
This course is 100% online, and there will be no physical classes. This course can be accessed through the web on any device.
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