Artificial intelligence courses are a crucial tool for training a workforce for lucrative jobs in a fast-growing sector.
Clearly, artificial intelligence has become necessary for scaling organizations across all industries. Yet there is a lack of trained professionals who have the skills to deploy AI efficiently for business purposes – hence the need for AI courses.
Those interested in utilizing AI have access to a wealth of knowledge through online courses taught by industry leaders such as Andrew Ng and IBM.
In this guide, we provide a list of top AI courses you can enroll in today, along with an overview of AI itself and details about the potential benefits of learning AI.
On a related topic: What is Generative AI?
Also see: Generative AI Startups
Best AI Courses Overview
Regardless of industry or level of experience, there’s an AI-specific course out there to fit your needs. Here, we break down some of the best AI course options so you can make the right choice.
Course | Overview | Cost |
Artificial Intelligence for Business |
|
$99.99 / or Udemy subscription |
AI for Everyone by DeepLearning.AI |
|
$49 |
Elements of AI by The University of Helsinki |
|
Free |
Introduction to AI by IBM |
|
$39 per month |
Applied AI Professional by IBM |
|
$39 per month |
Data Science: Machine Learning by Harvard University |
|
$99 with a certificate |
AI, Business & the Future of Work by Lund University |
|
$49 with a certificate |
Deep Learning Specialization by DeepLearning.AI |
|
$49 per month |
AI Nanodegree by Udacity |
|
$399 per month |
Complete Machine Learning & Data Science Bootcamp |
|
$109.99 |
Artificial Intelligence for Business (Udemy)
The Artificial Intelligence for Business course is offered through Udemy and covers how you can solve real-world business problems using AI algorithms. The course includes concepts such as building optimization models, implementing online learning and leveraging AI for business decision-making.
This course is best for those with a basic understanding of math and beginner-level Python programming knowledge.
AI for Everyone by DeepLearning.AI (Coursera)
AI for Everyone is a beloved course by famed expert Andrew Ng. In this course, Andrew takes you through the meaning behind AI terminology, what AI can do and what building machine learning models looks like.
This course is perfect for beginners who want an overview of what AI can do. However, it’s also a solid option for those experienced who want to build AI strategies for their organizations.
Also see: Generative AI Companies: Top 12 Leaders
Elements of AI by the University of Helsinki
The Elements of AI is a completely free option offered through the University of Helsinki. It includes two parts: Introduction to AI and Building AI. In the introduction, you’ll learn what AI is and what it can do. And in the second course, you’ll learn how to build AI algorithms.
This is a beginner-friendly course for those just getting started. However, some basic Python programming knowledge is helpful for the Building AI portion.
Introduction to Artificial Intelligence by IBM (Coursera)
Brought to you by the innovators at IBM, the Introduction to Artificial Intelligence course explores use cases for AI and its concepts. While you can complete this course separately, it’s also a part of in-depth programs, such as the Applied AI Professional Certification program.
This course was made for those without technical experience. You’ll also complete a mini-project to showcase your newfound AI skills.
On a related topic: The AI Market: An Overview
Applied AI Professional by IBM (Coursera)
The Applied AI Professional is a certification program by IBM. If you’re looking to quickly start a new career in AI, this is the course option for you.
Inside the program, you’ll learn all the concepts of AI. You’ll also create AI chatbots and build AI services using IBM Watson. Upon completion, you’ll receive a certificate from IBM.
Data Science: Machine Learning by Harvard University
Machine learning is a critical concept to understand if you wish to utilize AI. The Data Science: Machine Learning course by Harvard University takes you through the basics of machine learning and how to build a complete recommendation system.
This course is a great primer on machine learning and how you can use it for AI-specific use cases. It’s an introductory course, great for those without much technical expertise.
AI, Business & the Future of Work by Lund University (Coursera)
If you want to understand what the future of AI looks like, the AI, Business & the Future of Work course might be for you. You’ll learn how AI supports decision-making and how AI may affect your industry, so you can be prepared. As a beginner-level course, no prerequisites are required.
Also see: ChatGPT: Understanding the ChatGPT ChatBot
Deep Learning Specialization by DeepLearning.AI (Coursera)
Like machine learning, deep learning is an important concept to understand for the development of AI tools. The Deep Learning Specialization includes five courses that discuss concepts such as neural networking, improving neural networks, structuring machine learning projects and more.
After completion, you’ll receive a certificate. This course is specific to those with intermediate experience, including Python programming skills.
Artificial Intelligence Nanodegree by Udacity
The AI Nanodegree by Udacity includes three months of study. During that time, you’ll learn how to write programs using AI algorithms. Other concepts covered include classical search, automated planning, optimization issues and adversarial search.
Complete Machine Learning & Data Science Bootcamp (Udemy)
If you want to cover virtually every concept involved with artificial intelligence, this bootcamp is a solid option. The Complete Machine Learning & Data Science Bootcamp covers data science, data analysis, machine learning, AI and Python.
Starting with Machine Learning 101, this course fits the beginner’s needs perfectly. Plus, it includes two learning paths: one for those who know programming and one for those that don’t.
For more information, also see: Top AI Startups
AI Course FAQs
Understanding AI and where to start often results in many questions. Below, we answer some of the most frequently asked questions, so you can move forward with confidence.
Is AI Difficult to Learn?
Artificial intelligence requires the knowledge of complex concepts such as machine learning, programming and neural networking. Due to this complexity, AI can be quite challenging to fully learn.
The best way forward is to start with an introductory course on AI to learn the basics. Then, you’ll have the foundation you need to dive into the more complex concepts mentioned above.
How Do I Start an AI Career?
The first step is learning AI and how to use it properly. You can do so by taking various courses or enrolling in an AI-specific program. The next step is to determine your AI career path.
There are various AI job opportunities and many more will likely be opening up. Some examples include machine learning engineering, AI programming, and robotics engineering. Once you select a career path, you can determine what next steps you must take to reach your goal, such as obtaining additional certifications or applying for open roles.
Learn more: AI vs. Algorithms
Does AI Require Coding?
Taking an introductory course to learn how AI algorithms work and their use cases won’t typically require coding. However, if you plan to start a career in AI, you’ll need to understand programming languages such as Python and Java to build algorithms and machine learning models.
What Is Artificial Intelligence?
Artificial intelligence is the practice of using machines and algorithms to simulate human intelligence. Through AI and machine learning, machines can learn from data inputs and provide insights for problem-solving and decision-making.
There are various subsets of AI, such as generative AI and discriminative AI:
- Generative AI is the method of using algorithms to create new content in the form of text, photos and more.
- Discriminative AI discriminates between different classes of data to enable logistic regression.
Learn more: Generative AI Examples
Artificial intelligence is used across various industries to perform a variety of tasks. For example, AI may be used in manufacturing for predictive analytics. Or, AI could be used in healthcare to provide customized patient care plans.
Are There Benefits to Learning Artificial Intelligence?
The above use cases require professionals with a deep understanding of AI, including its use, potential benefits, implications and challenges. Gaining this understanding is the key benefit of learning AI. Learning enables these individuals to both champion and properly steward AI’s use across an organization.
Another benefit of learning AI is the development of skills that are in high demand. For AI to be used effectively, organizations must quickly close the AI-specific skills gap. Professionals looking to take their careers to the next level may be able to do so by understanding AI and how to build and use it.
On a related topic: Top Natural Language Processing Companies
The Bottom Line: AI Courses Provide a Career Boost
Learning AI through an online course will enable you to understand its benefits, challenges and use cases. As a result, you can start a new career in AI or simply work to utilize AI within your current organization. Truly understanding AI will ensure you use it effectively and safely, regardless of the use case or industry.