Prompting ChatGPT seems straightforward, but turning these capabilities into effective tools requires a deeper understanding. Free online AI courses make it easy for anyone to start learning how to use and understand Generative AI. But with so many options, it can be hard to know where to begin.
This article provides an overview of the best free AI courses in 2024. Whether you are just starting out, trying to improve your business or deepen your expertise, this guide will help you find the right course for your goals. To further assist you, we have compiled an organized Google sheet with a wide selection of free AI courses, allowing you to filter and choose the option for you.
What AI Is
Artificial Intelligence (AI) refers to the development of systems and machines that can perform tasks typically requiring human intelligence. While AI doesn’t truly "think" or "act" like a human, it can process data, recognize patterns, and make decisions based on programmed logic or learned experience.
Even though there is no single definition of AI, it is widely agreed that AI systems are both autonomous and adaptive. This means they can perform tasks in complex environments without needing constant user input and can learn from their experiences, improving their performance over time. These qualities enable AI to handle a wide range of applications, from personal assistants like Siri to advanced systems used in healthcare and finance.
When you start looking into AI, you will come across several key concepts that are important to understand. Here’s a breakdown of some of the most common terms:
- Machine Learning (ML): The foundation of AI, where systems learn from data and get better at tasks over time. This technology powers things like product recommendations on websites and email spam filters.
- Deep Learning (DL): A more advanced form of ML that uses Neural Networks to process complex patterns. DL is behind breakthroughs like facial recognition and self-driving cars.
- Neural Networks (NN): The building blocks of DL, designed to work similarly to the human brain by processing information through layers of interconnected neurons. Large Language Models (LLMs): Special types of DL models focused on understanding and generating human language. These models, like GPT (Generative Pre-trained Transformer), are used in tasks like chatbots, content creation, and language translation.
- Generative AI: AI systems that create new content like text, images, or music by learning patterns from existing data.
Many of these concepts overlap, making it hard to distinguish between them at times. To clarify, the following chart offers a visual representation of the broad AI field and shows, for example, where tools like ChatGPT fit within it.
Why AI Matters
Such technologies can help businesses to automate routine tasks, improve decision-making, and boost efficiency. For example, AI can enhance customer service through personalized experiences and fine-tuning marketing strategies. Beyond automating processes, AI empowers businesses to make more accurate, data-driven decisions that boost productivity.
Moreover, AI adoption is not just about efficiency. It has been shown to increase job satisfaction by allowing employees to focus on more creative and strategic tasks, rather than repetitive work.
AI skills are increasingly valuable, with companies offering higher salaries to those who master these technologies. As AI adoption grows, learning about AI is essential not only for career advancements but also for future-proofing businesses.
Free AI Courses
The following Top 10 AI courses for 2024 are curated to cater to varying depths of knowledge. The Top 5 AI courses are designed for beginners to provide clear, accessible learning for anyone looking to grasp the fundamentals of AI, regardless of any technical know-how. Following these, the remaining 5 courses are aimed at intermediate learners who want to advance their skills, covering more specialized AI domains, like prompt engineering for example.
Each course, lasting at least one hour, strikes a balance between being informative yet not too niche, some of which can be accessed for free via trial periods (e.g. Coursera offers a 7 day trial) — just remember to cancel in time to keep them cost-free. Whether you're new or refining your skills, there's something valuable here for everyone.
Beginner Courses
1. Introduction to AI (Elements of AI)
The Introduction to AI course, part of the Elements of AI series by MinnaLearn and the University of Helsinki, is a free online program designed to teach essential AI concepts, regardless of any prior knowledge. It covers AI's potential, limitations, and societal impact without requiring advanced math or programming. However, Python knowledge is optional for those who want to delve deeper into certain exercises. The course takes around 30 hours to complete, offers a free certificate at the end, and includes engaging graphics and a variety of exercises to enhance the learning experience.
2. AI for Everyone by Andrew Ng (DeepLearning.AI)
AI for Everyone, created by Andrew Ng on Coursera, is a non-technical course designed to help professionals and business leaders understand AI’s impact. It covers foundational AI concepts, project workflows and ethical considerations. The course offers a free certificate via Coursera, and it takes approximately six hours to complete. Learners gain insights into how AI can be applied in various industries, helping them identify opportunities and challenges in business contexts.
3. Introduction to AI (IBM)
Introduction to AI by the International Business Machines Corporation (IBM) on Coursera is a comprehensive beginner-level course covering ML, DL, and NNs. It offers hands-on projects to help learners apply what they’ve learned in practical scenarios. The course takes approximately 13 hours to complete and provides the option to earn a paid certificate, making it a great choice for those seeking foundational AI knowledge with real-world relevance.
4. Introduction to Generative AI - Art of the Possible (AWS)
This free course by Amazon Web Services (AWS) offers a beginner-friendly introduction to generative AI, focusing on its ability to produce new content such as text, images, and more. One unique aspect of the course is its detailed exploration of specific generative AI models like GPT and DALL-E, explaining how they function and their role in content creation. The course takes approximately 1 hour to complete and includes the option to earn a free certificate, making it a quick yet insightful way to explore the possibilities of generative AI.
5. Google AI for Anyone (Google)
The course, led by Laurence Moroney, Google’s Lead AI Advocate, offers a thorough introduction to fundamental AI concepts and their practical applications in both daily life and business. A key focus is placed on the role of data in AI, showing how data quality impacts performance and exposing the risks of poor data. It takes approximately 16 hours to complete and is self-paced for flexible learning. While the course is free, learners have the option to pay for a certificate. This makes it a good fit for individuals seeking a straightforward, non-technical overview of AI.
Intermediate Courses
6. Prompt Engineering for ChatGPT (Vanderbilt University)
This free course from Vanderbilt University on Coursera teaches the fundamentals of crafting effective prompts for AI systems like ChatGPT. It covers key techniques in prompt design, optimization, and prompt patterns, enhancing interactions with LLMs for tasks such as writing, coding, and problem-solving. The course, which takes approximately 18 hours to complete, is accessible to learners without a technical background and offers a free certificate upon completion.
7. Generative AI with LLMs (AWS & DeepLearning.AI)
Generative AI with LLMs, a collaboration between AWS and DeepLearning.AI, is a 3-module course that dives into prompt engineering, model fine-tuning, and real-world deployment, with instruction from AWS AI practitioners who actively use AI in business applications. Learners will explore the latest research on generative AI, gaining an understanding of how companies create value with cutting-edge technology. Designed to take approximately 16 hours to complete, it’s recommended for those with basic Python experience to maximize learning. The course is free to audit on Coursera, with a free certificate available as well.
8. CS50's Introduction to Artificial Intelligence with Python (Harvard)
Harvard University's CS50's Introduction to Artificial Intelligence with Python covers typical key AI concepts as well as search algorithms and their optimization. Through practical Python projects, learners apply these techniques in areas like game development, handwriting recognition, and machine translation. Though listed as an introductory course, it requires prior programming experience in Python or completion of CS50. The course is time-intensive, requiring 10-30 hours per week over 7 weeks, but it provides a comprehensive, high-quality learning experience. It’s free to audit, with an option to earn a certificate for $299 , providing a respected credential from Harvard.
9. AI Fundamentals for Non-Data Scientists (University of Pennsylvania)
Offered by the Wharton School of Business on Coursera, AI Fundamentals for Non-Data Scientists is part of the AI for Business Specialization and provides business professionals with a practical introduction to AI. Over 9 hours across 5 modules, learners use tools such as Teachable Machine and TensorFlow to explore AI’s role in handling big data, building algorithms, and improving accuracy. What sets this course apart is its inclusion of real-world insights from industry leaders at established companies like McDonald's and Visa, offering learners a unique look at how AI is applied in large-scale business operations. A free certificate is of course also available through Coursera.
10. Building AI (Elements of AI)
Building AI, the second part of the Elements of AI series, is a course designed to help learners build their own AI models and applications. The course offers flexibility, allowing participants to move between three difficulty levels—ranging from multiple choice exercises for non-programmers to Python-based projects for those with programming experience. Taking approximately 50 hours to complete, the course covers topics like machine learning, neural networks, and AI problem-solving through hands-on projects. While no advanced programming is required, some familiarity with basic AI concepts is recommended. At the end, learners have the option to purchase a certificate to verify their achievement.
Full AI Course List
Our compiled Google sheet offers a wider selection, comparing each course’s key topics, target audience, knowledge level, and any prerequisites. The sheet also highlights the time commitment required and whether a certificate is available (and if it's free). Most of these courses are self-paced, delivered through video or text, so you can learn at your own convenience.
Resources for Further Learning
Beyond structured courses, online communities and forums are invaluable for AI knowledge exchange and problem-solving. Platforms like Stack Overflow, Reddit's r/MachineLearning, and AI-focused Discord servers enable users to connect with experts, ask questions, and stay current with the latest developments. In addition to these interactive spaces, newsletters like Superhuman, The Neuron Daily, and Prompt Engineering Daily can help you to stay up-to-date.
On Twitter, accounts like KDnuggets (tutorials and resources), OpenAI (research updates and demos), and AssemblyAI (speech recognition and NLP deep dives) offer accessible insights into AI advancements.
Open-source projects and repositories on platforms like GitHub provide practical exposure to real-world AI applications. Notable repositories include TensorFlow, PyTorch, and Hugging Face's Transformers library, which are invaluable for learning and experimentation.
These multimedia resources can complement formal coursework by providing diverse perspectives and real-world context to theoretical concepts learned in free AI courses.
FAQ
Can I learn AI without any coding skills?
Yes, many beginner courses require no coding and cover essential AI concepts and applications. Tools like Google Cloud AutoML and IBM Watson Studio also allow users to build AI models without programming.
Are AI course certificates valuable for career growth?
Certificates from platforms like Coursera and edX, especially from reputable universities, can enhance your resume and demonstrate a commitment to learning AI. While they’re not equivalent to a formal degree, they’re often recognized by employers as indicators of specialized skills.
What AI skills are most in-demand?
Skills in ML, NNs, data analysis and natural language processing are highly valued. For non-coders, AI strategy, prompt engineering, and data ethics are increasingly important as they support the use of AI without technical expertise.
How long does it take to learn AI basics?
Most introductory AI courses range from 5-30 hours. Shorter courses, like AWS’s Introduction to Generative AI, take under 10 hours, while more intensive programs, like Harvard’s CS50 AI, may require several weeks.