AI (artificial intelligence) is one of the most important fields in technology today. It is hyper-present in today’s digital landscape. It has not only permeated the internet but also several sectors, including but not limited to gaming, healthcare, finance, manufacturing, and e-commerce.
With such a profound level of permeation, it is more than ever important now to understand and have knowledge of AI. Fortunately, even if you are a complete beginner, there are numerous ways to learn about AI.
Yes, you can read books on the topic. However, AI updates and develops with every passing day, so the concept of AI in books might be outdated. If you are looking for a more dynamic and updated way to learn about AI, then online courses are your best friends.
You can find a variety of AI courses and certifications on the internet. These are offered by some of the top tech firms and Ivy League schools. The courses cover everything from basic topics like introduction to AI to more complex ones such as reinforcement learning and neural networks.
DeepLearning.AI is one of the top learning platforms, founded by Andrew Ng, one of the leading and most prominent personalities in the field of AI. The platform has a plethora of courses on AI that you can take without paying a dime. The courses are for everyone, from complete beginners to advanced professionals.
These courses also come with a completion certificate, however, that might require you to purchase the full course.
However, if your goal is to widen your knowledge base, then you can enrol yourself in these courses for free. In this article, we will look at some of the top AI courses available on DeepLearning.AI.
List of FREE DEEP LEARNING AI COURSES in 2024
| Course Name | Duration | Level | Key Topics | Course Link |
| Generative AI for Everyone | 3 hours | Beginner | Generative AI Tools, AI Strategy for Work and Business, AI Strategy, How Generative AI Works, AI Productivity, AI Beyond Prompting | Gen AI for Everyone |
| Learn the fundamentals of generative AI for real-world applications | NA | Intermediate | Generative AI Tools, AI Strategy for Work and Business, AI Strategy, How Generative AI Works, AI Productivity, AI Beyond Prompting | GenAI for real-world applications |
| AI for Everyone | 6 hours | Beginner | Workflow of Machine Learning Projects, AI Terminology, AI Strategy, Workflow of Data Science Projects | AI for Everyone |
| Generative AI for Software Development | 15 hours | Intermediate | LLMs (Large Language Models), Generative AI, Machine Learning, Software Development, Software Engineering | GenAI for Software Development |
| Evaluating and Debugging Generative AI Models Using Weights and Biases | 1 hour | Intermediate | Instrument a Jupyter notebook, Manage hyperparameter config, Log run metrics, Collect artifacts for dataset and model versioning, Log experiment results | Evaluating & Debugging GenAI Models Using W&B |
1. Generative AI for Everyone
What We Like
- Taught directly by Andrew Ng.
- Good for beginners who are starting out.
- Includes hands-on exercises for real-world application.
- Clearly explains complex concepts.
What We Don’t Like
- Some advanced content is optional, which might lead to gaps in learning.
- Course duration of only three hours may not cover all topics in depth.
About the course: The course will cover the basics of generative AI. Some of the key topics covered by the course include how generative AI works, its potential applications, and its impact on various industries. With an emphasis on real-life application, you will learn about the potential and limitations of generative AI along with methods for good prompt engineering. The course provides an in-depth introduction, coupled with videos, quizzes, and hands-on activities.
COURSE DETAILS
| Provider | DeepLearning.AI |
| Duration | 3 hours |
| Level | Beginner |
| Description | “Instructed by AI pioneer Andrew Ng, Generative AI for Everyone offers his unique perspective on empowering you and your work with generative AI.” |
| Key Topics | Generative AI Tools, AI Strategy for Work and Business, AI Strategy, How Generative AI Works, AI Productivity, AI Beyond Prompting |
2. Learn the fundamentals of generative AI for real-world applications
What We Like
- Taught by expert AWS AI practitioners.
- Focus on practical, real-world applications of generative AI.
- In-depth coverage of the LLM-based generative AI lifecycle.
- Hands-on experience with advanced techniques and tools.
- Suitable for various professionals, including data scientists, machine learning engineers, and prompt engineers.
What We Don’t Like
- Course content may be too specialized for those seeking a broader overview of AI.
- Only course audit is available for free.
About the course: This is an intermediate course recommended to those with Python knowledge. The course made in collaboration with AWS (Amazon Web Services), covers important topics such as data gathering, model selection, performance evaluation, and deployment. You will also learn about the transformer architecture that drives LLMs and techniques for fine-tuning and scaling laws based on experience in optimization. The course focuses on hands-on experience with state-of-the-art training, tuning, and deployment methods. It also tackles difficulties and openings generative AI brings to businesses.
COURSE DETAILS
| Provider | DeepLearning.AI in collaboration with AWS |
| Duration | NA |
| Level | Intermediate |
| Description | “In Generative AI with Large Language Models (LLMs), created in partnership with AWS, you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.” |
| Key Topics | Generative AI Tools, AI Strategy for Work and Business, AI Strategy, How Generative AI Works, AI Productivity, AI Beyond Prompting |
3. AI for Everyone
What We Like
- Is accessible to all skill levels.
- Provides a clear overview of AI technologies and their applications.
- Includes real-world examples and case studies.
- Covers both AI strategy and societal impacts
- Instructed by AI pioneer Andrew Ng.
What We Don’t Like
- Limited depth for those with technical backgrounds.
- Requires a paid subscription for a completion certificate.
About the course: Taught by Andrew Ng, the course provides an overview of AI aimed at non-technical professionals. It explains AI technologies, machine learning workflows, and data science processes in a way that can be understood by anyone. It also covers the impact of AI in different areas and on society as a whole, including possible biases and ethical aspects. The course includes basic AI ideas, practical examples from the world, and methods to put AI into action in an organization.
COURSE DETAILS
| Provider | DeepLearning.AI |
| Duration | 6 hours |
| Level | Beginner |
| Description | “AI for Everyone, a non-technical course, will help you understand AI technologies and spot opportunities to apply AI to problems in your own organization.” |
| Key Topics | Workflow of Machine Learning Projects, AI Terminology, AI Strategy, Workflow of Data Science Projects |
4. Generative AI for Software Development
What We Like
- Taught by Laurence Moroney, an AI expert with experience at Google.
- Covers practical applications of generative AI tools like GitHub Copilot and ChatGPT in software development.
- Provides hands-on projects, including pair coding, code analysis, and database implementation.
- Focuses on improving coding skills, optimizing code quality, and developing innovative software solutions.
What We Don’t Like
- Focuses primarily on generative AI’s role in software development, with less emphasis on broader AI concepts.
- Details on cost and financial aid options are not provided upfront.
About the course: The course covers how generative AI technologies can improve and make software development easier. Laurence Moroney, the instructor, provides real use cases for generative AI tools, such as GitHub Copilot and ChatGPT, explaining to learners how these tools can be integrated at different stages from design until deployment. This course is divided into three main parts: understanding generative AI, using AI for pair coding and code analysis, and creating complex software solutions. It focuses on practical application through projects like code optimization and database implementation, to enhance coding efficiency and creativity.
COURSE DETAILS
| Provider | DeepLearning.AI |
| Duration | 15 hours |
| Level | Intermediate |
| Description | “Generative AI is transforming software development by enhancing and augmenting traditional coding practices.” |
| Key Topics | LLMs (Large Language Models), Generative AI, Machine Learning, Software Development, and Software Engineering |
5. Evaluating and Debugging Generative AI Models Using Weights and Biases
What We Like
- Focus on practical skills using Weights & Biases (W&B), a popular platform for ML operations.
- Covers essential aspects of machine learning workflow management, such as tracking experiments, hyperparameter management, and versioning.
- Offers hands-on learning through the instrumentation of Jupyter notebooks and the use of platform-independent tools.
What We Don’t Like
- The course is brief, which might limit the depth of coverage on more advanced topics.
- Need familiarity with LLMs and generative image models.
About the course: This is an intermediate course that teaches the basics of using W&B for ML operations. During this course, you will learn how to instrument a Jupyter notebook, manage hyperparameter configurations, and log run metrics into an experiment dashboard with W&B. You also get hands-on experience collecting artifacts for dataset and model versioning as well as trace interactions with large language models (LLMs). The course gives a step-by-step introduction to boost effectiveness and handle complex AI projects better.
COURSE DETAILS
| Provider | DeepLearning.AI |
| Duration | 1 hour |
| Level | Intermediate |
| Description | “This course will introduce you to Machine Learning Operations tools that manage this workload. You will learn to use the Weights & Biases platform which makes it easy to track your experiments, run and version your data, and collaborate with your team.” |
| Key Topics | Instrument, a Jupyter notebook, Manage hyperparameter config, Log run metrics, Collect artifacts for dataset and model versioning, Log experiment results |
Conclusion
DeepLearning.ai is a free platform with several courses available on different topics, ranging from generative AI to machine learning and delving into more complex topics. It doesn’t matter if you are just starting out or are an experienced professional with years of experience under your belt, the courses we have listed above are some of the best ones to get started with AI. The best thing about this is that the courses are free to enrol in, so, you do not even have to burn a hole in your pocket.
Recommended reading:
List of Stanford University AI Courses for FREE
Best Google AI Courses and Certifications for FREE
Best Microsoft AI Courses and Certifications for FREE
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