Courses

Best Amazon AI Courses and Certifications for FREE in 2024

Amazon is not just an e-commerce company, but also a major player in the AI industry. It also has a ton of free courses on AI that you can take advantage of to enhance your skills and knowledge. This article will look at the best Amazon AI courses and certifications for free.

Artificial Intelligence (AI) is everywhere. At every nook and cranny of the internet, you will find either an AI tool or content generated by the said tool. It can be an image, an essay, music, or video. Not only the Internet but different sectors such as healthcare, finance, logistics, and more have started incorporating AI in their operations to enhance productivity and efficiency. 

With this level of intrusiveness, it is vital to learn about AI, what it is, its potential, and its drawbacks. Luckily, there are thousands of courses and certifications on AI available on the internet. Some of these are presented by top schools and organizations, such as Stanford, Google, Microsoft, and Amazon. These courses cover a range of topics, from beginner-friendly subjects like introduction to AI, to more advanced ones like machine learning, neural networks, and natural language processing.

Amazon is not just an e-commerce company, but also a major player in the AI industry with their development of products like Alexa and Amazon Web Services (AWS). It has a ton of free courses on AI that you can take advantage of to enhance your skills and knowledge. If you are a student who is looking to build a career in AI or a professional wanting to climb the career ladder, these courses will help you out. 

Let’s take a look at the best Amazon AI courses and certifications for free. 

LIST OF FREE AMAZON AI COURSES in 2024

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1. Introduction to Generative AI – Art of the Possible

What We Like

  • Comprehensive introduction to generative AI.
  • Available in multiple languages.
  • Practical examples to illustrate concepts.

What We Don’t Like

  • Limited to a beginner level, may not suit advanced learners.
  • No detailed information on specific applications or tools.

About the Course: The course “Introduction to Generative AI – Art of the Possible” provides a basic introduction to generative AI. It emphasizes its possible applications, risks, and advantages. The course has real-world examples to show how generative AI can work in business contexts. The best thing about the course is that it is completely free and available in different languages. Even though it is made for beginners, this course is perfect for people interested in generative AI. 

COURSE DETAILS 

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2. Generative AI with Large Language Models

What We Like

  • Instruction from expert AWS AI practitioners.
  • In-depth coverage of generative AI, including transformer architecture and empirical scaling laws.
  • Practical skills for deploying AI in real-world applications.
  • Structured learning with videos, readings, and assignments.
  • Available in 21 languages.

What We Don’t Like

  • Requires prior knowledge of Python and basic machine learning concepts.
  • Focuses primarily on large language models (LLMs), which might not cover all aspects of generative AI.
  • Requires payment to receive the completion certificate.

About the Course: This intermediate course on generative AI covers large language models (LLMs) and their practical uses in detail. It is instructed by skilled AWS AI professionals who will guide you through the complete process of generative AI, from collecting data and picking models to evaluating performance and setting up. Some of the key topics included in the subject include transformer design, methods for fine-tuning, and empirical scaling laws. The course has a combination of videos, readings, and assignments to help you learn. However, you need prior knowledge of Python and basic machine learning to fully take advantage of the course.

COURSE DETAILS 

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3. Introduction to Machine Learning in AWS

What We Like

  • Sufficient coverage of cloud computing, AWS, and machine learning.
  • Includes practical demonstration for better understanding.

What We Don’t Like

  • Limited to foundational concepts, and may not suit intermediate or advanced learners.
  • Focuses primarily on AWS, not covering other cloud service providers in depth.
  • Self-paced nature might lack interaction and support.

About the Course: This beginner-friendly course covers the grassroots of cloud computing, AWS, and machine learning. It explains what cloud computing is, explores different cloud service providers, and provides an in-depth look at AWS and machine learning concepts. The course also has practical demonstrations and examples to enhance your core understanding. 

COURSE DETAILS 

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4. AWS Machine Learning Foundations

What We Like

  • Comprehensive coverage of machine learning fundamentals and advanced topics.
  • Hands-on experience with AWS AI devices (DeepLens, DeepRacer, DeepComposer).
  • Practical training on preparing, building, training, and deploying ML models using Amazon SageMaker.
  • Emphasis on software engineering best practices and object-oriented programming.

What We Don’t Like

  • Might be overwhelming for absolute beginners due to the breadth of content.
  • Requires access to AWS AI devices, which may not be readily available to all learners.
  • Might be outdated as the course was released in 2022.

About the Course: The course covers the basics of machine learning. It covers topics like computer vision, reinforcement learning, and generative AI. It offers hands-on learning experience with AWS AI gadgets such as DeepLens, DeepRacer, and DeepComposer. Plus, you will receive real-life training from Amazon SageMaker to learn how to prepare models as well as train and deploy them. The course expands on software engineering methods, including clean code, efficient coding techniques, refactoring skills, documentation habits as well as version control methods. It also covers testing procedures and how to manage logging and code assessments. Moreover, it also introduces object-oriented programming which allows learners to construct their own Python packages. 

COURSE DETAILS 

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5. Building a Generative AI-Ready Organization

What We Like: 

  • Beginner-friendly with no prior experience required.
  • Focuses on organizational readiness for generative AI, tailored for business leaders and decision-makers.
  • Provides practical actions to prepare for generative AI.

What We Don’t Like:

  • Limited to a single module, which may not cover all aspects in depth.
  • Content might not be fully translated into other languages.

About the Course: The goal of this courseis to give business leaders and decision makers the necessary knowledge and tools for a successful adoption of generative AI. The course emphasizes on making shared vision and getting ready organizational structures, giving useful understanding into how to blend generative AI with business activities. It covers important topics like AI, cloud governance, and cloud operating models. It contains one module, one reading and one assignment. 

COURSE DETAILS

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6. AWS: Introduction to Machine Learning on AWS

What We Like

  • In-depth introduction to AWS services for machine learning.
  • Hands-on lab exercises available in the Verified Certificate track.
  • Focuses on practical applications of AI, ML, and deep learning.
  • Covers a wide range of AWS tools and services (Rekognition, Textract, Comprehend, Transcribe, Translate, Lex, SageMaker).
  • No prerequisites required.

What We Don’t Like

  • Hands-on exercises are restricted to the Verified Certificate track.
  • Learners from specific countries (Iran, Cuba, Crimea region of Ukraine) cannot register due to U.S. sanctions.

About the Course: This course is for software developers and engineers who are starting with AWS services. It covers various AWS services such as Amazon Rekognition, Textract, Comprehend Transcribe Translate Lex SageMaker etcetera. You will receive video introductions along with hands-on exercises and video walkthroughs. After completing this course, you will be able to understand how to use AI and ML in different jobs, analyze labels and images, and host your own ML models with Amazon SageMaker. 

COURSE DETAILS

7. Learn about AI/ML

What We Like

  • Covers a wide range of topics from introductory to advanced AI/ML concepts.
  • Provides hands-on learning with practical exercises and lab sessions.
  • Includes training for both business leaders and technical specialists.
  • Detailed training on AWS tools like SageMaker, Comprehend, Textract, and more.

What We Don’t Like

  • Some courses and certifications are not available in certain countries due to sanctions.
  • Verified Certificate track courses may have associated costs.

About the Course: This course by AWS is for learners with different levels of skill, from beginners to professionals. It focuses on boosting knowledge about AI and ML, using AWS services AWS services to implement, manage, and optimize these technologies. The curriculum has digital classes that include key tools like Amazon SageMaker, Amazon Comprehend, Amazon Textract and others. Also, it it offers specialized learning plans for developers, technical and business leaders as well as AWS partners. 

COURSE DETAILS

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Best 20 Free AI Courses For Beginners

8. Intro to Machine Learning in AWS for Beginners

What We Like

  • Includes fundamental AWS services and machine learning concepts.
  • Designed for absolute beginners with no prior knowledge required.
  • Hands-on learning experience with practical exercises using Jupyter Notebooks and Amazon SageMaker.
  • Prepares students for opportunities in various industries adopting ML.
  • Covers a wide range of AWS tools and services, including SageMaker, S3, EC2, and more.

What We Don’t Like

  • The total course duration might be too short for in-depth learning.
  • Access to some features and advanced content may require payment.

About the Course: This course is for beginners who are passionate about technology and want to get into machine learning using AWS. It covers the basics of important AWS services like S3, EC2, IAM, and CloudWatch, as well as the advantages of cloud computing and what you can do with the AWS Free Tier Package. You will understand how to make a new account on AWS, move around in the AWS Management Console, and grasp the basics of machine learning, knowing the differences between artificial intelligence (AI), machine learning (ML), data science (DS), and deep learning (DL). It also includes information on Amazon SageMaker’s components as well as its training choices. The course includes tutorials to show you how to use AWS SageMaker Studio, SageMaker JumpStart, SageMaker Autopilot, and SageMaker Data Wrangler.

COURSE DETAILS

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From foundational courses to advanced certifications, Amazon provides a diverse range of learning opportunities tailored to various experience levels and career goals. These courses not only equip learners with cutting-edge AI techniques and tools but also ensure they are well-prepared to tackle real-world challenges in the ever-evolving tech industry. By taking advantage of these free educational resources, individuals can stay ahead in the competitive AI landscape and drive innovation within their organizations.

Recommended reading:

Top AI in Healthcare Courses

List of Stanford University AI Courses for FREE

Best Google AI Courses and Certifications for FREE 

Best Microsoft AI Courses and Certifications for FREE 

List of Coursera AI Courses for FREE by Big Tech Companies 

Disclaimer: If you purchase through Tech Chilli affiliate links, we may earn a commission at no additional cost to you.

This post was last modified on August 19, 2024 9:33 am

Raya

Raya is a tech enthusiast diving deep into New-Age technology, especially Artificial Intelligence (AI) and Machine Learning (ML). She is passionate about decoding the complexities and uses of new-age tech. Raya is on a mission to write articles that bridge the gap between technical jargon and everyday understanding, making AI and ML accessible to a wider audience.

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