If you’re looking for the best Artificial Intelligence (AI) online classes, this article is for you.
AI is growing exponentially as we rely on it more and more to provide solutions in every professional domain. Because of this, you’ve probably heard that developing skills in AI will help you gain an edge in your career.
There are so many AI courses out there, it can seem difficult to decide which course to choose. But narrowing down on one course is actually very easy if you know what you’re currently capable of.
Have you never written a line of code but want to learn more about AI? Are you familiar with AI terminology and want to start experimenting with some AI tools? Do you already know a coding language and want to start building some AI algorithms?
In this article, I collated a series of 10 articles while taking into consideration these different starting points. So you can find the best course for you no matter your background.
With that in mind, let’s get started.
What is the best AI course?
Here are my top AI course recommendations:
- Introduction to AI & Building AI (Elements of AI)
- AI for Everyone (Coursera)
- CS50's Introduction to Artificial Intelligence with Python (Harvard and EdX)
- Artificial Intelligence A-Z™: Learn How To Build An AI (Udemy)
- Deep Learning and Neural Networks with Python (Skillshare)
- Generative AI Art For Beginners: Midjourney & the tactics of killer text prompts (Skillshare)
- Python for Data Science, AI & Development (Coursera)
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)
- Build Basic Generative Adversarial Networks (GANs) (Coursera)
- Artificial intelligence in Digital Marketing (Udemy)
How I decided
First and foremost, all the courses here are great for different things. So I’ve organized the list according to accessibility and breadth of coverage.
I’ve placed courses that require few or no prerequisites, along with courses that cover a wider range of AI uses, at the top of the list. Further down you'll see more advanced courses (for the most part) which are a little more specific in the content covered.
The two part course from Elements of AI is my top choice because it’s free, and it's the most accessible. Complex concepts are simplified so people without a tech background can understand them. As such, it provides an excellent and well-rounded introduction to all the key concepts of AI.
Coursera's AI for Everyone is next. It covers a broad range of topics in AI, explains them succinctly, yet is slightly more geared towards people who are looking at implementing AI in their work, especially in the business field. It can also be taken for free if you don’t require the certificate.
Third is Harvard and EdX’s CS50 Introduction to Artificial Intelligence with Python course. An absolutely amazing course worth your time if you have prior experience coding in Python but want a solid course that guides you to becoming a proficient AI coder.
Best free AI course : Introduction to AI & Building AI (Elements of AI)
- Amazing detailed and easy to understand explanations of key AI concepts
- Includes practical exercises that people from all backgrounds can participate in
- Part 2 includes an option of tailoring the difficulty level based on your previous experience coding with Python
There are plenty of ways in which you can get introduced to AI for free. The two-part Elements of AI course is one option. It provides you with a great informative base for understanding how AI works and how it can impact society.
If you're looking to get a little more hands on, but don’t want to spend too much money up front, you can opt to audit courses on Coursera or edX. Or subscribe to Skillshare’s free trial.
Best AI online courses reviews
1. Introduction to AI & Building AI (Elements of AI)
Platform: Elements of AI | Course length: written content and tests totalling to approximately 120 hours
Elements of AI is an initiative created by the University of Helsinki and the online learning platform MinaLearn. The aim is to help make AI learning more accessible to people from a wide range of backgrounds. The course includes two parts. Part 1 is more informative and theoretical, while Part 2 is more hands-on, so there is something for everyone.
Introduction to AI teaches participants about AI, what it is composed of, what it can do, and its implications. Building AI is a more hands-on experience. And depending on the level you chose, you can even start programming with Python.
What you'll learn:
- What is AI
- Problems AI can solve
- What is Machine Learning
- What are Neural Networks
- The Future of AI and its societal implications
- How you can use numerical and textual data in Machine Learning
- How to use Math concepts like logistic regression with neural networks
- How Deep learning works
- Very good breadth of material. The class covers all the most essential aspects of AI in theory and in practice
- Easy to understand explanations
- Amazing UI (User Interface) design
- Part 2 is customisable. You have three difficulty levels that you can choose from depending on you familiarity with Python
- Option to receive a free certificate after class completion
- Variety of exercises which allows for better information retention
- All course content is written. If you prefer learning through video or auditory, the class format might not be what you are after
- Part 1 could be too easy if you are already familiar with most AI terminology and concepts
- Part 2 could be quite challenging if math isn’t one of your strong suits
Who it’s for: A perfect option if you want to learn more about AI, hold knowledgeable conversations, learn about how your business could benefit from AI technology, or get started at coding some of your first AI algorithms. Bear in mind that all the teaching content is written. So if you aren’t the biggest fan of reading, this might not be for you. But don’t worry, because we’ve got plenty of other options.
Overall: Provides the opportunity to go from learning the definition of AI, to creating your first AI projects. The two-part class is highly customisable, as you can choose to begin either at Part one (if you lack basic AI terminology and concepts), or skip to Part 2 if you want to learn more about the real-world applications of AI. Since you have three levels to choose from in Part 2 depending on your programming abilities, you are certain to find something that suits your level and learning goal.
2. AI for Everyone (Coursera)
E.g. Platform: Coursera | Teacher: Andrew Ng | Course length: 35 video lessons totalling 4 hours and 30 minutes
Andrew Ng is the founder of DeepLearning.AI, Chairman of Coursera and a professor at Stanford University. He has co-authored over 100 academic papers on machine learning, robotics and related fields. Andrew also used to work as the Chief Scientist at Baidu, the founding lead of the Google Brain team.
As both a leading practitioner in the field of AI, and an experienced professor, you can be certain that this course’s teaching quality and content is going to be excellent.
What you’ll learn:
- The basics of Machine learning and data usage in AI
- How your job and business can benefit from AI
- How to work in an AI team and what tools to get
- How smart speakers and self-driving cars work
- The problems you could encounter with AI
- Societal impacts of AI
- Clarity of instruction
- Great for understanding how to apply AI in your current work
- Looks at business considerations with AI, eg how to build an AI team
- Includes a segment on the societal impact of AI
- No complicated math
- Focuses more on quality than quantity, so might not suit people seeking a quick overview
- Designed and explained in layman's terms, so it could be too easy for you if you already know lots of AI terminology
- There is a fee for receiving the certificate at the end
Who it’s for: Ideal if you know very little about AI and need an introductory course that explains how AI could benefit your work. Also a perfect option if you want to gain a working knowledge of AI so that you can better communicate and delegate tasks to software engineers at work. Since some of the course content can apply to the other aspects of the IT sector, it’s also a great opportunity to review some basic IT concepts.
Overall: A great non-technical course for those intrigued by the prospects of using AI at work. As one of the shorter courses in this list, it's one of the faster options for learning about fundamental AI concepts, such as neural networks, machine learning, deep learning and data science.
3. CS50's Introduction to Artificial Intelligence with Python (Harvard and EdX)
Platform: EdX | Teachers: David J. Malan, Brian Yu | Course length: 7 video lessons totalling 10 hours and 49 minutes
This course is offered by Harvard University, frequently ranked in the top ten best universities in the world for computer science.
The course itself is taught by two amazing teachers. David Malan, is a computer science professor in Harvard’s School of Engineering and Applied Sciences who also teaches at Harvard’s Business and Law Schools. Brian Yu comes from a background of computer science, linguistics and education, which really helps
What you’ll learn:
- Key concepts, algorithms, and data structures used to search
- To understand how AI computes logic and linguistic subtleties (like sentences, inferences, etc)
- How to use probability-based methods to provide logical solutions in uncertain situations
- To apply optimization for AI algorithms
- How to use machine learning to predict future outcomes with high accuracy
- To incorporate neural networks into your AI programming
- Extremely comprehensive and clearly explained
- Practical learning – you get to create algorithms, and use AI coding notions of classification, optimization, reinforcement learning and more
- A great balance between theory and practice
- Can be taken alone or as part of Harvard’s CS50 series of introductory courses in computer science
- Option of getting a Harvard certificate (which will look amazing on your resume) upon course completion
- One of the more advanced courses on this list, so not suitable for people with zero coding knowledge
- Might find it very difficult to follow if you aren’t very math savvy
Who it’s for: As one of the most advanced courses on this list, it’s great if you’re familiar with Python, and really want to dive into the world of AI by coding cool AI projects. Whilst you don’t need to be a math whizz, the course will be easier to complete if you have a solid understanding of elementary logic.
Overall: This class provides students with both quantity and quality. The syllabus is packed with all the most useful concepts to use in AI programming, while the instruction is impeccable. After completing this course, you will have a solid level of expertise in AI programming.
4. Artificial Intelligence A-Z™: Learn How To Build An AI (Udemy)
Platform: Udemy | Teachers: Hadelin de Ponteves, Kirill Eremenko, Luka Anicin | Course length: 124 video lessons totalling 16 hours and 57 minutes
This course is delivered by three passionate teachers; Hadelin de Ponteves, Kirill Eremenko and Luka Anicin. Each of them approach the topic of AI with their own unique background, from data science, to AI engineering. With ratings of 4.5/5 stars, they have accumulated over 4 million students combined. These three are clearly skilled at their craft of transferring their passion for AI.
You’ll learn to:
- Code from scratch
- Incorporate Q-learning and A3C into AI building
- Master fundamental AI principles
- Build a virtual self-driving car
- Code from intuition instead of theory and complicated math
- Create AI that can win games
- Clear and detailed explanations
- Clear step-by-step guide on how to build AI
- Great insights into available techniques
- Practical content
- Impeccable explanations of what AI is all about
- Released in 2017 and uses an older python version
- Requires a high-school level of math
- Tricky if you have zero coding knowledge
Who it’s for: Ideal for anyone who is ready to get their hands dirty with some actual AI coding. You'll absolutely love it if you learn by doing. Since it includes some background knowledge, it’s also a great refresher for people who are familiar with AI, but still require clarification on some of its basic concepts and vocabulary. You will get a lot more out of this course if you have some basic Python coding experience.
Overall: An amazing course that allows you to dive straight into AI programming, with relatively few prerequisites (though some coding experience does make the course easier to understand). Taught by three highly rated teachers, it delivers clear, detailed and fun explanations. Making it easier for people from vastly different backgrounds to understand and apply the course content.
5. Deep Learning and Neural Networks with Python (Skillshare)
Platform: Skillshare | Teacher: Frank Kane | Course length: 25 video lessons totalling 4 hours and 24 minutes
Even though you don’t see AI in the title, this course couldn’t be more relevant. It focuses on Deep Learning and Neural Networks, two of the most fundamental aspects of AI (if you are unfamiliar with these concepts, I would recommend taking the introduction to AI from Elements of AI mentioned above before taking this course).
The class is taught by Frank Kane, a former developer for Amazon and IMDb who created the AI algorithms that provide us with personalized movie and product recommendations. He is the founder of Sundog Software, a tech company that creates virtual reality products.
You’ll learn to:
- Develop neural networks for handwriting recognition
- Create AI software that predicts your political party based on your votes
- Perform sentiment analysis on real movie reviews
- Build deep neural networks and build your first deep learning project
- Use Tensorflow and Keras software
- Understand Generative Adversarial Networks and how to use them
- Hand on practice with some code
- Explains difficult concepts clearly
- Makes developing AI feel surprisingly easy
- Short sharp course which doesn’t waste time on things you’ll never use
- Great tips to continue developing your AI coding skills once you have completed the course
- Requires understanding of some basic algebraic concepts, eg Gradient Descent, Autodiff and Softmax (does include brief explanations, but you might want to supplement it with Google searches if you aren’t math savvy)
- Requires prior programming experience with Python (see our best Python courses review)
- Could include a little more explanation on hyperparameters, to better understand what to use them for
Who it’s for: A perfect crash course if you are a straight-to-the-point type of person with some Python experience, and want to start building your first AI projects without any preamble. If you want to see how to use neural networks and deep learning in a practical way, this course is for you. While you do need to understand some algebraic concepts, you don’t need to be a mathematician to take this course
Overall: One of the quickest ways to learn how to develop your own AI programs. You get a solid introduction to some of the practical usages of Neural Networks, Generative Adversarial Networks and Deep Learning, which makes it easier to transfer some of the skills learned to your own ideas for AI programs.
6. Generative AI Art For Beginners: Midjourney & the tactics of killer text prompts (Skillshare)
Platform: Skillshare | Teacher: Oliver Theobald | Course length: 11 video lessons totalling 54 minutes
AI art may not be the first thing you think about when you hear “AI”. But it’s definitely worth considering if you don’t know how to code, and want to start getting your hands dirty right away.
AI art is a great way of starting your AI learning journey, since no previous coding or art experience is required. All you need to do is write a description (called a prompt) of what you want to see, and let the AI software generate an image based on this description.
The class itself is taught by Oliver Theobald, an expert in AI and Cloud Computing who has also become a bestselling author after publishing Machine Learning for Absolute Beginners.
What you’ll learn:
- To navigate Midjourney, free AI art software, and produce your first piece of AI art
- To write a good prompt to make your art look just the way you want
- How to use modifiers to get your final piece to look exactly how you imagined it
- About frames and how to use them
- Detailed and clear explanations
- Step-by-step demos to guide you
- Accessible to anyone with a computer and doesn’t require any prerequisites
- An amazing hands-on way for someone unfamiliar with any coding languages to experience the power of AI, how it works and what its current limits are
- Great short introduction on fundamental components of AI
- Very narrow class content that focuses mainly on AI art
- The course focuses on Midjourney software. Though it does include a quick demo on Craiyon, and does mention other software
- Doesn't teach any coding basics
Who it’s for: Perfect if you prefer learning by doing but don’t yet have the skills to start developing your own algorithms and AI systems. An interest in art is definitely a plus. A great option if you don’t want to put too much time and effort into learning about AI, but still want to grasp the basics.
Overall: A perfect hands-on introduction to simple AI concepts and applications. Allows you to start exploring what AI can help you create, as well as what it can’t do. Also teaches some art theory and terminology to help write prompts. With this course, you'll experience an original and engaging approach to AI. It will definitely be a conversation starter.
7. Python for Data Science, AI & Development (Coursera)
Platform: Coursera | Teacher: Joseph Santarcangelo | Course length: 15 video lessons totalling 1 hours and 43 minutes
The Python for Data Science, AI & Development class is offered as part of 10 IBM certification streams. But you can also opt for the individual course if you don’t want to complete an IBM full certificate.
The course itself is taught by Joseph Santarcangelo, who is an expert in Machine Learning at IBM. With an overall score of 4.6/5 out of almost 30,000 ratings, you know it’s worth your time.
What you’ll learn:
- Python basics
- How to use integers, numbers and strings
- To use Python to work with data
- To create functions with Python
- Hands-on focus
- Video lessons are well explained
- Everything taught is useful – no time wasted on concepts you'll barely use
- Brings you from a complete beginner to someone with workable python skills
- Tasks are quite easy and the final assignment isn’t closely related to the course content
- Some content is a little outdated, which makes it harder to follow with newer software updates
- Covers the basics of coding more than AI coding, but this can be expected from a beginner course
Who it’s for: Perfect if you already know quite a lot about AI and its history, and actually want to get started with coding. Ideal if you are a self-motivated individual who would like to gain the tools needed to play around with AI.
Overall: Provides a solid Python foundation to start exploring more advanced courses. Some of the content is taught using older software, which requires a little bit of external research. But since the course does not blather on about things you won’t use, it's a perfect teaching structure for you to follow, even if you do end up supplementing some of the teaching materials with some google searches.
8. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)
Platform: Coursera | Teachers: Laurence Moroney | Course length: Mix of video lessons, readings and quizzes totalling in 23 hours
Laurence Moroney is the head of AI Advocacy at Google. His focus is making AI accessible to developers and expanding career opportunities in Machine Learning. He's also written dozens of books on programming, including ‘AI and ML for Coders’.
This course is a perfect next step for anyone who took Andrew Ng’s “AI for Everyone” course, as it will allow you to put the foundational principles you learned in Andrew Ng’s course into practice. The course focuses on TensorFlow software and its neural network library, Keras, and serves as an introduction for anyone wanting to build scalable models to apply to real-world problems.
You’ll learn how to:
- Use TensorFlow to build scalable AI-powered algorithms
- Understand and implement Machine Learning, Deep Learning and computer vision
- Refine your code by using convolutional neural networks to enhance the vision and handling of real-world images.
- Use ImageDataGenerator and explore the impact of compressing images.
- A good introduction course to building convolutional neural networks
- Simple and easy to understand explanations
- Incremental structure meaning you always build on what you've just learned
- Straight to the point, practical and directly applicable to real-world problems.
- Lots of hands-on practice and visuals to support learning
- Certification available
- Uses an older version of TensorFlow
- The instructor does not cover TensorBoard and how to debug a faulty model
Who it’s for: Those new to TensorFlow and Keras, who are looking for a basic introduction to the concepts. The course has a great balance between theory and practice, so it's perfect for people who want to get their hands dirty, but need a solid understanding of key concepts to retain what they learned in practical exercises.
Overall: A great way for beginners to begin experimenting with deep learning, machine learning and computer vision. The course is well designed, practical and provides a solid level of expertise in TensorFlow and Keras. Overall, the course is a great balance of theory and practice that will give you a solid understanding of the fundamental concepts of AI programming.
9. Build Basic Generative Adversarial Networks (GANs) (Coursera)
Platform: Coursera | Teachers: Sharon Zhou | Course length: Mix of video lessons, readings and quizzes totalling in 35 hours
Sharon Zhou has worked with Andrew Ng at Stanford, at Google and other startups, so she has a lot of experience in artificial intelligence. She’s also carried out projects in the medical and environmental fields.
If you are interested in Generative Adversarial Networks (GANs) (machine learning models that can generate realistic image, video, and voice outputs), it’s worth looking into this course.
What you’ll learn about:
- What GANs are and their real-world applications
- Fundamental components of GANs and how to build them using PyTorch
- Deep convolutional GANs and how to use different functions to improve your GAN architecture
- Advanced techniques to reduce instances of GAN failure
- To effectively control GANs, modify the features in a generated image and build conditional GANs
- Good and clear insight into the world of GANs
- Good balance between encouraging and challenging content
- Assignments are very clear and adaptable: they allow you to go as shallow or as in-depth as you want
- Excellent practical insight, focusing on what GAN algorithms do, rather than the structure and theory behind them
- Explains the basics of calculus and algebra, so you don’t need to be a math whizz to take this class
- Certificate available
- Focuses on a very specific aspect of AI
- Requires a self-learner and motivated attitude since it includes lots of reading
- Forums and Slack channel aren’t very active
- Coding assignments might be too easy for more advanced coders
Who it’s for: If you are looking for a solid introduction into GANs, have a little experience programming and writing machine learning code, this would be a great course for you. Especially if you are a hands-on learner, as it includes a lot of practical examples and exercises. Best for self-learners who likes learning from a variety of materials, such as videos, readings, and practical exercises.
Overall: You will learn about the different types of GAN and how they work. And you’ll also get hands-on experience building and training your own GAN using PyTorch. Another great thing about this class is that it does not require prior knowledge of advanced math or machine learning.
10. Artificial intelligence in Digital Marketing (Udemy)
Platform: Udemy | Teacher: Srinidhi Ranganathan | Course length: 67 video lessons totalling 10 hours and 50 minutes
Taught by the CEO of First Look Digital Marketing Solutions (India's First Artificial Intelligence Powered Digital Marketing company), this course provides a unique perspective and skillset on how AI can help in the Digital Marketing field.
With Digital Marketing being in the top ten most in-demand jobs on LinkedIn in 2022, being able to apply AI to Digital Marketing is a strategically unique way of upskilling yourself for today’s job market.
You’ll learn to:
- Create augmented reality experiences with apps
- Curate articles using AI
- Create a search engine
- Use AI powered platforms to gain insights on which leads to pursue and attract more clients
- Create your own AI powered voice-assistant without any code
- Create a social network platform
- Use AI technology to generate faster pitches
- Will introduce you to a variety of useful AI websites you can use for digital marketing
- You will learn to use AI tools that make your daily marketing activities easier and faster
- Gain insight into the future of AI in marketing and advertising
- Information taught is very practical and can be used right away
- Courses go straight to the point, so no unnecessary blabber
- Doesn’t require prior experience in coding
- Does not cover theory or basic AI concepts. This is not a course where you will learn about AI, but rather one where you will learn how to apply AI generators in digital marketing
- Can be a bit repetitive (but this also allows you to retain course content better)
- Includes a few technical issues, such as problems syncing
- Some of the tools covered in the course must be paid for
Who it’s for: A great option for a current or aspiring digital marketing professional looking to upskill. Similar to Frank Kane’s course on AI generated art mentioned above, this course is for you if you want to get your hands dirty right away, don’t have previous coding experience, and want to gain practical knowledge that can be directly applied in your work.
Overall: This course will provide you with an amazing overview of how you can apply AI software and generators in a non-traditional AI industry. As AI usability continues to extend into marketing, art, politics and more, this course provides a practical case study of how AI can be used outside of traditional AI industries such as engineering or math.
What are the advantages of taking an Artificial Intelligence Course?
- Career opportunities: Since the demand for AI professionals continues to increase, taking an AI course can open up new career opportunities in traditional data science fields such as computer science, data analysis, and machine learning. But with the adaptability that AI has to offer, professionals in other areas such as psychology, charities and education could also benefit from bringing the effective solutions that Ai can bring to their own fields.
- Problem-solving: AI allows you to solve complex problems. So taking a course in AI will give you the skills to apply AI techniques to real-world problems and build more efficient frameworks for solving future issues.
- Multidisciplinary: AI is multidisciplinary and combines lots of areas of expertise, like computer science, mathematics, engineering, and more. A course in AI will expose you to different perspectives, so that you’ll be able to communicate effectively with diverse teams and experts.
- Business innovation: AI is rapidly transforming multiple industries, so taking a course will give you an edge in understanding how AI can benefit you and your business. Taking a course in AI can also help you develop the skills to build relevant AI solutions.
- Personal Growth: AI is a rapidly growing field, taking an AI course will not only help you develop new skills but also enable you to think critically and creatively, and stay ahead of the curve in today's rapidly changing technological landscape.
Buyers guide: what to look out for
- A course that resonates with your personal goals: To stay motivated, choose a course that aligns with what you wish to achieve. If you want to learn about AI, its terminology and its uses, but aren’t particularly interested in coding, it’ll be hard for you to stick to a hands-on course that uses a lot of terminology and concepts you aren’t familiar with. Similarly, if you’re an experienced coder, you might not find more theoretical and informative courses stimulating for your level of expertise.
- Consider your current experience before selecting a course: It will be quite hard for you to stick to a more intermediate or advanced course if you don’t have a basic understanding of the basics of AI, such as machine learning and neural networks. As a beginner, if you are more of a hands-on person but have little theoretical knowledge, pick one of the courses in the list that also includes an option to try out some code, such as the Building AI course or the Generative AI Art for Beginners course
- Consider the course content and projects: Make sure that the hands-on projects from these courses are projects you’ll like working on. There are so many different courses that cover different ways to apply AI, so make sure you select a perspective that is interesting to you.
- Identify how you learn best: Do you learn best through reading or watching videos? Do you retain things better if you can apply them in exercises or in programming projects? Do you learn better by jumping straight in and coding, or do you need a little theory before you can understand how to build models? Consider all of these aspects when reading through course descriptions to ensure you’ll get the most out of the course you chose.
How much does it cost?
The course list above has a wide price range, so it is up to you to decide how much you are willing to spend on your AI learning journey.
Some of the courses mentioned are completely free. For instance, both of the courses from Elements of AI don’t cost a dime. So they’re a great start if you're curious about upskilling yourself, but aren’t quite ready to commit your money.
Coursera is a great option if you want to have the choice to pay or not. Coursera courses can be taken for free if you don’t want the certificate. The price range for a course certificate is usually around $49.
You also have the possibility of purchasing an annual subscription to Coursera. This gives you access to more than 7,000 courses, specializations, professional certificates and guided projects on many different topics. The cost for this is only $399 per year.
edX is a similar option to Coursera. It also includes courses taught by leading institutions like Harvard, Stanford etc. You can choose to audit these for free, but you can also opt for a certificate which usually costs around $149. You can also choose to get a premium account, which costs $345 per year. But think about how much that costs compared to a Harvard Summer course!
Skillshare costs $165 per year. It is a platform where experts offer 40,000+ courses to share their skills. Udemy’s 204,000+ courses can be purchased singly for around $20-60. Or you can purchase membership for $26.99 per month to receive full access to 6,000 top courses.
How long does it take to learn AI?
The amount of time it takes to learn about AI varies depending on your background, how long you are willing to commit to studying, and what your goals are.
If you simply want to learn about AI and its terminology, basic construction and social uses, many online courses allow you to get a solid understanding of underlying concepts in under 3 months.
However, if you want to learn how to create AI, the amount of time it takes depends on your background. With little or no experience, it can take six months or even a year of consistent study and practice to develop a strong understanding of the basics of AI, such as data science, machine learning, neural networks, and how different applications work.
If you have a background in computer science or a related field, you may be able to pick up the basics more quickly. However, it can still take several months of structured study and practice to become advanced in the field.
Like many fields, there isn’t a clear time frame for how long it takes to learn AI. Since it is an ever evolving field, being proficient in AI requires the attitude of a life-long learner, as you will need to be willing to update your knowledge as the field of AI progresses.
AI might seem overwhelming to break into, but fortunately there are loads of options out there for your knowledge and expertise level.
As a beginner, you can start off with the two part Elements of AI course, and come back to this review later to see in which direction you want to progress.
With a bit of Python coding knowledge, there are loads of options you can choose from. “CS50's Introduction to Artificial Intelligence with Python” by Harvard and EdX is great if you’re after a more traditional, academic approach to AI.
If you’re after a complete course that covers everything you might need, try the “Artificial Intelligence A-Z™: Learn How To Build An AI” on Udemy.
Or if you want to try out something creative, go for the “Generative AI Art For Beginners” course on Skillshare; it won’t take too much of your time. Interested in AI for marketing? Look at the “Artificial intelligence in Digital Marketing” course on Udemy.
There are so many ways to go with AI, and hopefully this article has helped guide you towards a decision on which AI course is best for you!.
Best AI Courses – Frequently asked questions
The two part course from Elements of AI is the highest on the list, as it is the most accessible course to people with all different backgrounds.
The price ranges between $0 and $99 for a solo course. If you opt for an annual subscription to a platform instead of going for a one-off purchase, the price ranges between $26.99 and $399.
An AI course takes between 54 minutes and approximately 120 hours to complete.
Ella is a recent Graduate from King’s College London’s BA programme in War Studies and Philosophy.