Google, AWS, & IBM are offering free AI courses for techies Enthusiastic to get high paid jobs in 2024; apply now

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In a rapidly evolving digital landscape, artificial intelligence (AI) has become a crucial skill for success in the IT industry. To help techies stay ahead of the curve, leading tech giants like Google, Amazon Web Services (AWS), and IBM are offering a range of free AI courses to upskill professionals and prepare them for the jobs of the future.

Also, Read: Accenture Online Internship: For Everyone, Free Certificate Apply Now 2024

Google, AWS, & IBM are offering free AI courses for techies Enthusiastic to get high paid jobs in 2024; apply now

Also,Read: SBI Summer Internship 2024: For College Students, Apply Now

Here Google, AWS, & IBM are offering free AI courses

1.Introduction to Artificial Intelligence

Artificial intelligence (AI) is all around us, seamlessly integrated into our daily lives and work. In this course, you will uncover the fundamentals of AI, explore its diverse applications, and understand how it is transforming different industries. You’ll learn the basics of generative AI and explore its use cases and applications.

This course covers core AI concepts, including deep learning, machine learning, and neural networks. You’ll examine generative AI models, including large language models (LLMs) and their capabilities. Furthermore, you’ll examine AI’s application across domains such as natural language processing (NLP), computer vision, and robotics, uncovering how these advancements drive innovation and use cases.

This course discovers the transformative impact of AI, including generative AI, on businesses. Additionally, you’ll understand how AI can revolutionize your work and environment and what career opportunities are arising through AI.

Finally, the course explores AI ethics and governance and prevalent concerns and issues surrounding the AI landscape. The course includes hands-on labs and a project, providing an opportunity to explore AI’s use cases and applications. You will also hear from expert practitioners about the capabilities, applications, and ethical considerations surrounding AI.

Course Link Click Here

2.AI For Everyone

AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone–especially your non-technical colleagues–to take.

In this course, you will learn: – The meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science – What AI realistically can–and cannot–do – How to spot opportunities to apply AI to problems in your own organization – What it feels like to build machine learning and data science projects – How to work with an AI team and build an AI strategy in your company – How to navigate ethical and societal discussions surrounding AI Though this course is largely non-technical, engineers can also take this course to learn the business aspects of AI.

Course Link Click Here

Also, Read : Google Free New Latest courses 2024: For Everyone Enroll Now

Also, Read : 6 Free AI Classes You Can Take Online From Top Tech Firms, Universities

3. Introduction to Generative AI

This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

When you complete this course, you can earn the badge displayed here! View all the badges you have earned by visiting your profile page. Boost your cloud career by showing the world the skills you have developed!

Course Link Click Here

4. Generative AI with Large Language Models

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.

By taking this course, you’ll learn to: – Deeply understand generative AI, describing the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection to performance evaluation and deployment – Describe in detail the transformer architecture that powers LLMs, how they’re trained, and how fine-tuning enables LLMs to be adapted to a variety of specific use cases – Use empirical scaling laws to optimize the model’s objective function across dataset size, compute budget, and inference requirements –

Apply state-of-the-art training, tuning, inference, tools, and deployment methods to maximize the performance of models within the specific constraints of your project – Discuss the challenges and opportunities that generative AI creates for businesses after hearing stories from industry researchers and practitioners Developers who have a good foundational understanding of how LLMs work, as well the best practices behind training and deploying them, will be able to make good decisions for their companies and more quickly build working prototypes. This course will support learners in building practical intuition about how to best utilize this exciting new technology.

This is an intermediate course, so you should have some experience coding in Python to get the most out of it. You should also be familiar with the basics of machine learning, such as supervised and unsupervised learning, loss functions, and splitting data into training, validation, and test sets. If you have taken the Machine Learning Specialization or Deep Learning Specialization from DeepLearning.

AI, you’ll be ready to take this course and dive deeper into the fundamentals of generative AI.

Course Link Click Here

Also, Read: 4 Practice Tests for any C++ Certification – (Free Course)

Also, Read: 10 Best Free Online Courses With Certificates In 2024 Enroll Now

5. Machine Learning Specialization

The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications. 

This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.

This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. 

It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.)

By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.

Course Link Click Here

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