There’s no escaping it—artificial intelligence is revolutionizing our lives and work. Indeed, according to market research firm Marketsandmarkets, the global AI market is projected to reach a staggering $407 billion by 2027. Accordingly, this transition to AI-led jobs is transforming careers old and new.
However, while AI has quickly become ubiquitous, many businesses still lack experts who fully grasp its potential. With AI’s applications set to expand into increasingly niche domains, this problem isn’t going anywhere.
For job seekers, finding the best AI courses is a savvy tactic. Upskilling in this new tech can help whether you want to change to an AI career path completely or simply want to future-proof your skills for a competitive edge.
From overarching introductions to AI to its applications across various job roles and deep dives into the technical aspects of applied AI, this post outlines a few of the best AI courses to suit your needs.
- Why learn AI?
- The 11 best online AI courses
- Key takeaways
Ready to take the next step in your career and unleash the power of AI? Explore our carefully curated list of the best AI courses online in 2023.
1. Why learn AI?
To most, it should be clear by now that artificial intelligence (AI) is definitely not just a buzzword or fad—it’s reshaping how we work. Understanding its fundamentals can bring benefits to your career, regardless of your background or future plans.
For non-technical professionals
While AI was once limited to technical roles (at least during its earlier development), improvements in user interface design and the rolling out of these systems on a mass scale now mean that non-technical professionals can use them in various contexts.
Tools like Bard and ChatGPT are excellent examples of this, but they are far from the only ones. Others include AI-powered virtual assistants, automated content curation systems, and marketing analytics platforms.
Some practical advantages of learning AI as a non-technical professional include:
- Accessible decision-making: AI-driven data analytics is now highly accessible and requires little to no technical expertise. Anyone—from marketing professionals to HR and business managers—can now use AI-driven insights with minimum effort.
- Better collaboration: With the world of work growing ever more complex, interdisciplinary collaboration has become increasingly necessary. Understanding the principles of AI and how it works will help you to communicate more effectively with technical team members.
- Process automation: AI can automate routine and repetitive tasks, such as data entry, document processing, or customer inquiries. AI can streamline workflows, whatever job you work in.
For business enthusiasts
For C-suite professionals or aspiring business leaders, AI can aid growth and maximize your profitability in various ways:
- Competitive edge: Adopting AI—whether developing in-house tools or using them to streamline your business operations—can provide a competitive advantage.
- Entrepreneurial potential: It may seem like AI is already everywhere, but the revolution is just beginning! Knowledge of AI is already sparking countless new business ideas, with many startups focusing on AI-driven solutions in areas ranging from security to robotics.
- Risk management: AI-powered analytics can assess and mitigate risks in real time. Business leaders—especially those in fields like finance, insurance, and IT—can use AI to identify potential threats to their organization and implement proactive strategies to manage them.
For technical roles
Of course, if you’re a technical professional—perhaps a software developer, data analyst, or machine learning engineer—AI courses present a great opportunity for updating your technical skills:
- AI development: Understanding AI algorithms and languages like Python is essential if you’re interested in roles that involve developing or working with AI systems.
- Applied AI: AI isn’t just about coding—it’s about solving real-world problems. This is why fields like healthcare and finance are hiring increasing numbers of AI engineers and machine learning experts.
- Innovation in other technical roles: AI technical expertise isn’t limited to development roles. It can enhance areas ranging from web development to product design by streamlining processes and allowing you to develop AI-driven features, such as product-integrated chatbots and recommendation engines.
Whether you want to stay competitive in your field, seek strategic advantage in business, or are passionate about learning the latest tech, finding the best AI courses will help your career blossom, whichever direction it goes in.
2. The 11 best online AI courses
Without further ado, here are our handpicked top 11 best AI courses available right now:
Best AI courses for beginners
Want to learn the basics of AI before exploring it on a deeper level? Here are three free courses of various lengths to suit your needs:
Time commitment: 10 hours
AI for Everyone, available on Coursera and led by renowned AI expert Andrew Ng, is the ideal course for non-technical professionals.
Offering a well-structured introduction to AI’s impact on business and society, it’s split into four non-technical modules. You’ll find the content approachable, and Andrew Ng’s teaching style simplifies what can be complex topics.
Start by demystifying common AI terminology—such as neural networks, machine learning, and deep learning—before focusing on what AI can and (crucially) cannot do!
This is a beginner-friendly and pragmatic choice for those who want a broad introduction to AI’s potential applications, what’s involved in building an AI project, and who want to understand the current ethical and social discourse surrounding AI.
Time commitment: 1 day
One of the first things to learn about this field is the practical aspects of responsible AI, and this course offers essential insights into AI ethics. Although focused on the experiences of Google Cloud engineers, the lessons are applicable beyond the platform.
Throughout the course, you’ll learn how Google approaches responsible AI, its best practices, and lessons learned from the company’s years of experience in the field. If you’re non-technical but nevertheless want to build a responsible AI strategy, it offers a great foundation.
Modules in the course include creating a business case for responsible AI, exploring technical considerations and ethical concerns, and setting up and running AI principle reviews (which involve evaluating operational principles in the deployment of AI systems).
Whether you’re working in a Google Cloud environment or not, you’ll find the course offers valuable and broadly applicable insights.
Time commitment: 16 weeks at 6 hrs/week
A longer free course delivered by renowned computer scientists Sebastian Thrun and Peter Norvig, this one is divided into two parts. The first focuses on AI fundamentals, where you’ll explore topics like machine learning, probabilistic reasoning, and advanced planning. While these are tricky topics for beginners, they’re delivered as accessibly as possible.
The second half of the course explores applications of AI, including computer vision, robotics, and natural language processing. It not only provides historical context but underscores AI’s continuous growth and uses in various industries, from gaming and journalism to finance, medicine, and quantum science.
Best AI courses for business leaders
If you want to understand how you can better leverage AI to support your business, here are three courses to consider checking out:
Time commitment: 6 weeks (around 10 hrs/week)
If you ever wanted to say you studied at Oxford, now’s your chance! The Oxford Artificial Intelligence Program, offered by the university’s Saïd Business School, is a comprehensive six-week online course, targeted at business leaders, IT managers, and technical personnel.
You’ll explore AI’s history, functionality, capabilities, and ethical considerations, all under careful guidance from some of the school’s most renowned faculty members and experts in AI.
You’ll look at AI’s wide-ranging applications and implications, learning to construct a compelling business case for its integration in your industry and organizational context. The course is certified by the UK CPD Certification Service, attesting to its rigor.
Furthermore, as a participant, you’ll enjoy an exclusive privilege—an all-access pass to the official Oxford Executive Education Alumni group on LinkedIn, a vibrant network of AI enthusiasts and professionals. Additionally, you’ll benefit from edX’s Career Engagement Network, which offers valuable resources and regular events to support your ongoing journey in the field.
Cost: $94.99 subscription fee (with regular discounts)
Time commitment: 15 hours
Artificial Intelligence for Business (+ ChatGPT Bonus) via Udemy is for any business professional looking to harness AI’s potential.
While it requires a basic understanding of high school math and Python programming, it’s also one of the more affordable options on our list. Divided into three parts, each module explores distinct business applications of AI using specific case studies to bring the learning to life.
“Optimizing Business Processes” looks at how you can use reinforcement learning to optimize workflows in an e-commerce warehouse. “Minimizing Costs” focuses on using AI to reduce energy consumption in data centers. Finally, “Maximizing Revenues” explores strategies for boosting income in an online retail business context. While the examples are quite specific, the principles are broadly applicable.
As a bonus, all participants receive a 100-page book: AI for Business. An excellent reference guide, it offers clear explanations of AI theory (using detailed math where required), case studies, code templates, and additional techniques and tips.
Time commitment: 6 weeks (6-8 hrs/week)
This self-paced online program from MIT Sloan School of Management provides a balanced perspective on AI, emphasizing its practical applications over the hype.
It offers a variety of learning approaches, including interactive videos, quizzes, presentations, assignments, and forums. Guided by a Success Adviser (who assists with time management and technical support) completion of the course results in a certificate from MIT Sloan School of Management.
In terms of topics, the course delves into contemporary AI technologies such as machine learning, natural language processing, and robotics, offering insights into their relevance for business. Furthermore, it explores AI’s impact on modern business strategy and addresses associated economic and societal challenges.
Crucially, the instructors stress AI’s role in augmenting the workforce, dispelling misconceptions about AI job displacement. The program also highlights the potential of collaborative human-computer intelligence in solving complex business problems.
Best AI courses for technical experts
If you’re a technical enthusiast eager to delve deeper into specific aspects of AI deployment, these courses will introduce you to some relevant technical skills:
Time commitment: 15 hours
This course provides a deep understanding of reinforcement learning on a technical level, connecting it to human psychology, and instructing you on the practical implementation of 17 distinct reinforcement learning algorithms.
Be warned, though—you’ll need solid programming and math skills before you start! However, presuming you have a foundation in calculus, probability theory, and proficiency using Python libraries NumPy and Matplotlib, you’ll find this course practical and technically in-depth.
Throughout the course, you’ll gain all the skills you need to apply supervised machine learning methods in reinforcement learning scenarios.
Although it’s not for beginners, the course meticulously explains every line of code. Plus, unlike many online courses, the instructor is accessible via email should you need clarification.
Cost: Audit for free
Time commitment: 3 months (10 hours/week)
The Natural Language Processing Specialization via Coursera offers an intermediate-level dive into the fascinating world of NLP.
With an option to audit for free, you’ll acquire a robust skill set, including learning how to implement sentiment analysis and word translation using techniques such as logistic regression, naïve Bayes, and word vectors. You’ll also delve into every day topics that we often take for granted, such as autocorrect and autocomplete.
Coursera’s specialization introduces advanced concepts such as how to use recurrent neural networks for tasks such as sentiment analysis, named entity recognition, machine translation, text summarization, chatbot development, and much more.
While the course will demand a lot of you, and you’ll need a working knowledge of machine learning, Python, calculus, algebra, and statistics, the payoff is substantial. By the end, you’ll have honed your expertise in some of the most important aspects of natural language processing.
Cost: Variable ($50-$300)
Time commitment: 3 weeks, 3-4 hours/week
Computer vision is a growing area of AI, with applications in self-driving cars, robotics, augmented reality, and facial detection systems.
This IBM course explores the foundational aspects of this fascinating field across these diverse use cases. You’ll master Python, Watson AI, and OpenCV for image manipulation and interact with various image classification models. Hands-on exercises are integral to the learning here, with everything delivered in a cloud environment provided at no additional cost.
Once you’ve completed the course, you’ll have the skills you need to develop and deploy your own computer vision web application. Although prior experience in machine learning isn’t necessary, a basic understanding of Python will help. Note, though, that available slots are limited at times.
New enrolment dates are regularly announced, though, so don’t be overly concerned if you encounter some temporary unavailability!
Time commitment: 8 weeks
Artificial Intelligence for Robotics via Udacity provides a comprehensive introduction to the practical applications of AI in the rapidly evolving field of robotics.
Once again taught by Sebastian Thrun (a prominent figure in autonomous driving research), this eight-week course covers fundamental AI concepts, including localization, Kalman and particle filters (which, for the uninitiated, are important statistical techniques!), search algorithms, PID control (a method for autonomously regulating systems), and SLAM (Simultaneous Localization and Mapping—commonly used in applications like self-driving cars and drones).
A notable aspect of this particular course is its strong emphasis on hands-on learning. You’ll apply theoretical knowledge through programming exercises and assignments, including a final project that involves pursuing a runaway robot.
Best of all, this course is entirely free, allowing you the flexibility to engage with the content at your own pace.
Time commitment: 2 months (15-20 hours/week)
CareerFoundry’s data analytics specialization offers an immersive experience in the world of machine learning. Designed for data analysts and scientists eager to harness the power of Python for machine learning, this course ensures a blend of theoretical knowledge and hands-on practice.
- Foundational Insights: Dive into the history and tools of machine learning, understanding its distinction within AI and the importance of ethics in the field.
- Supervised & Unsupervised Learning: Grasp the nuances of both learning types, their applications, and the role of regression in supervised learning.
- Complex Models with Keras: Set up intricate machine learning problems using Keras and TensorFlow, applying algorithms like Random Forests and Support Vector Machines.
- Hyperparameter Evaluation: Fine-tune deep learning models for optimal results by understanding and adjusting hyperparameters.
- Visual Machine Learning Applications: Integrate machine learning with image recognition and explore the potential of Generative Adversarial Networks (GANs).
One of the standout features is the 1:1 mentorship, where you’re paired with an industry expert. This personalized guidance ensures you’re not just learning but truly understanding and applying your knowledge. By the end, you’ll have a healthy machine learning portfolio, showcasing your skills and a certificate of completion to validate your expertise.
Prerequisites include a foundational knowledge of Python and familiarity with tools like Excel and Jupyter Notebook. For those keen on diving deep into machine learning and emerging with practical, job-ready skills, this course is a top contender.
Speak to a program advisor to get the full details.
3. Key takeaways
As we’ve learned in this post, artificial intelligence (AI) is evolving fast, shaping various industries along the way. If you want to stay ahead of the curve and keep your skills relevant for the 21st century, learning to apply AI in your specific business area is a smart plan.
Fortunately, as we’ve discovered, there are numerous online AI courses, each catering to a different AI-enthused audience.
For those completely new to the field of AI, there are many introductory courses. These offer insights into AI’s practical applications while demystifying its more complex concepts. Many also introduce AI’s impact on business, society, and broader ethical considerations.
Business leaders, meanwhile, may want to focus on AI’s strategic implications. There are AI courses to help here, too, each teaching a different aspect of AI for business, helping give your company a competitive edge in the market.
Finally, the more technically inclined will find courses catering to hard skills in specific domains of AI, such as computer vision, robotics, and natural language processing. Focusing on theoretical knowledge and applied AI, these courses are typically more complex. The trade-off is that they can open doors to exciting new opportunities within the field.
As AI advances, more industries will incorporate it into their operations, making AI skills increasingly valuable.
To learn about this important topic and its potential impact on future careers, check out the following introductory guides: