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AWS AI Practitioner Certification Course

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AWS AI Practitioner Certification Course

Name: AWS AI Practitioner Certification Course
Item: AWS AI Practitioner Certification Course
Rating: 5
Author: Vijay Kalkundri

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Step into the fascinating world of artificial intelligence and learn to build AI-powered solutions with AWS. Master the intricacies of this niche domain with our offering on the AWS Practitioner Course, which will help you prepare for the AWS AI Practitioner Foundational Examination. The key features of this course include:

Aligned with AWS Certified AI Practitioner Foundational (AIF-C01) Exam
24 Hours of Live Instructor-led Training
3+ Industry Use Cases, 20+ Hands-on Demos
5+ Assignments & Knowledge Checks
Capstone Project

Join us today to get hands-on experience with state-of-the-art AWS AI, ML, and generative AI services & acquire the proficiency to become a certified AWS AI engineer.

1k+ satisfied learners Read Reviews

Why should you take AWS AI Practitioner Certification Course?

According to a survey conducted by Amazon, 92% of the organizations across geographies will start using AI-powered solutions by 2028.

AWS certification is rated as one of the most popular and lucrative cloud certifications in IT globally - Global Knowledge Study.

As per Glassdoor, the average annual salary for an AI engineer in the US is USD201,350, with a cash bonus of USD70,522.

Curriculum

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

Hands-on:

Exploring AWS AI Services
Working with SageMaker

Skills 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

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AWS AI and ML Applications: Industry Use Cases

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

Hands-on:

AI Applications Across Industries
AI-Driven Business Solutions
Strategies for Integrating AI into Business Processes
AI, ML, and Generative AI Use Cases

Skills You Will Learn:

Practical AI Applications
Industry-Specific AI Solutions
Generative AI Techniques

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Machine Learning and Generative AI with AWS

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

Hands-on:

Building and Deploying ML Models with Amazon SageMaker
Evaluating ML Model Performance
Exploring Generative AI Foundation Models
Developing and Deploying Applications with Generative AI

Skills You Will Learn:

Model Development and Deployment
Build and deploy generative AI applications

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Generative AI with Amazon Bedrock and Amazon Q

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

Hands-on:

Building Generative AI Applications with Bedrock
Working with Amazon Q
Understanding Generative BI with Q and Quicksight

Skills You Will Learn:

Building Applications with Bedrock
Leveraging Amazon Q
Generative BI with Q and Quicksight

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Prompt Engineering for Generative AI Applications

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

Hands-on:

Designing and Modifying Prompts
Applying Prompt Engineering Techniques
Optimizing Inference Parameters
Identifying and Mitigating Prompt Misuses and Risks

Skills You Will Learn:

Effective Prompt Design
Prompt Engineering Techniques
Risk Management in Prompt Engineering

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Optimizing Foundation Models with RAG and Fine-Tuning

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

Hands-on:

Implementing Retrieval-Augmented Generation (RAG)
Optimizing Foundation Models with Fine-Tuning
Evaluating Model Performance

Skills You Will Learn:

Implementing and Evaluating RAG
Fine-Tuning Foundation Model
Model Optimization Techniques

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Advanced AWS Services for AI Application Development

Topics:

Advanced AWS Services for AI Application Development (Self-paced)
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

Hands-on:

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

Skills 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 CloudFormatio

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Security Compliance and Governance with AWS

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

Hands-on:

Implementing Data Governance and Compliance
Securing AI Systems

Skills You Will Learn:

Governance and Compliance in AI Systems
AI Security and Policy

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Responsible AI Practices and Principles (Self-paced)

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

Hands-on:

Applying Amazon Services for Responsible AI

Skills 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.

View course curriculum

Testimonial Reviews

Vijay KalkundriPrincipal Engineer at Reflektion, former Senior Test Engineer at Nokia

I had a great experience in taking the Hadoop course from Edureka. It is the only course in the mark ... Read More

Manish DunaniBig Data Enthusiast

It is a very good experience to learn from edureka!.Faculty seems excellent in sharing real world ex ... Read More

Joga RaoPrincipal Data Architect at AEMO

I am a Customer at Edureka. I attended the AWS Architect Certification Training, I found the trainin ... Read More

Praveen KonkisaBI Architect & Hadoop Specialist at Teradata

I have taken Informatica, Hadoop, R-programming, Spark and Scala and several other training's from p ... Read More

Gnana Sekhar VangaraTechnology Lead at WellsFargo.com

Edureka Data science course provided me a very good mixture of theoretical and practical training. T ... Read More

Sidhartha MitraIBM MDM COE Head @ CTS, Kolkata Area, India

Edureka has been an unique and fulfilling experience. The course contents are up-to-date and the ins ... Read More

Video Reviews

Vinayak shares his Edureka learning experience and how our Big Data training helped him achieve his dream career path.

Our learner Balasubramaniam shares his Edureka learning experience and how our training helped him stay updated with evolving technologies.

Sriram speaks about his learning experience with Edureka and how our Hadoop training helped him execute his Big Data project efficiently.

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Structure your learning and get a certificate to prove it.

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.

View course curriculum

Be future ready. Start learning

Structure your learning and get a certificate to prove it.

AWS AI Practitioner Certification Course

Why should you take AWS AI Practitioner Certification Course?

Curriculum

Exploring Artificial Intelligence on AWS

AWS AI and ML Applications: Industry Use Cases

Machine Learning and Generative AI with AWS

Generative AI with Amazon Bedrock and Amazon Q

Prompt Engineering for Generative AI Applications

Optimizing Foundation Models with RAG and Fine-Tuning

Advanced AWS Services for AI Application Development

Security Compliance and Governance with AWS

Responsible AI Practices and Principles (Self-paced)

About your AWS AI Practitioner Certification Course

What are the objectives of our AWS AI Practitioner Online Training?

What are the prerequisites for Edureka's AWS AI Practitioner Certification Training?

What is the syllabus of the AWS AI Practitioner Certification Course?

Do I need coding knowledge to take up this program?

What is the duration of the AWS AI Practitioner Certification Course?

What are the advantages of learning the AWS Certification Course from Edureka?

What are the system requirements for this AWS AI Practitioner Certification Course?

How will I execute practicals in this AWS AWS AI Practitioner Certification Course?

Testimonial Reviews

Video Reviews

AWS AI Practitioner Certification Course

What if I miss the AWS AI Practitioner Certification Course classes?

Will I get placement assistance after completing this AWS AI Practitioner Certification Course?

Who are the instructors for the AWS AI Practitioner Certification Course?

What if I have more queries after completing the AWS AI Practitioner Certification Course?

What if I miss a class of AWS AI Practitioner Certification Course?

What if I have queries after I complete this AWS AI Practitioner Certification Course?

How soon after signing up would I get access to the Learning Content?

Will the course material be available to learners after completion of the course?

Is this course 100% online? Do I need to attend any physical classes?

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