Since ChatGPT proved a consumer hit, a gold rush has set off for AI in Silicon Valley. Investors are intrigued by companies promising generative AI will transform the world, and companies seek workers with the skills to bring them into the future. The frenzy may be cooling down in 2024, but AI skills are still hot in the tech market.
Looking to join the AI industry? Which route into the profession is best for each individual learner will depend on that person’s current skill level and their target skill or job title.
When assessing online courses, we examined the reliability and popularity of the provider, the depth and variety of topics offered, the practicality of the information, the cost and the duration. The courses and certification programs vary a lot, so choose the options that are right for each person or business.
They are listed in order of skill level and, within the skill level categories, alphabetically. In most cases, each provider offers multiple courses in different aspects of generative AI. Explore these generative AI courses to see which might fit the right niche.
A name learners are likely to see on AI courses a lot is Andrew Ng; he is an adjunct professor at Stanford University, founder of DeepLearning.AI and cofounder of Coursera. Ng is one of the authors of a 2009 paper on using GPUs for deep learning, which NVIDIA and other companies are now doing to transform AI hardware. Ng is the instructor and driving force behind AI for Everyone, a popular, self-paced course — more than one million people have enrolled. AI for Everyone from Coursera contains four modules:
For individuals, a Coursera account is $49-$79 per month with a 7-day free trial, depending on the course and plan. However, the AI for Everyone course can be taken for free; the $79 per month fee provides access to graded assignments and earning a certificate.
Coursera states the class takes six hours to complete.
This course has no prerequisites.
Are you a C-suite leader looking to shape your company’s vision for generative AI? If so, this non-technical course helps business leaders build a top-down philosophy around generative AI projects. It could be useful for sparking conversation between business and technical leaders.
Free if completed within the Coursera 7-day trial. Otherwise, a Coursera account is $49-$79 per month, depending on the course and plan.
This course takes about one hour.
There are no prerequisites for this course.
This is a well-reviewed beginner course that sets itself apart by approaching AI holistically, including its practical applications and potential social impact. It includes hands-on exercises but doesn’t require the learner to know how to code, making it a good mix of practical and beginner content. Datacamp’s Understanding Artificial Intelligence course is particularly interesting because it includes a section on business and enterprise. Business leaders looking for a non-technical explanation of infrastructure and skills they need to harness AI might be interested in this course.
This course can be accessed with a DataCamp subscription, which costs $25 per person per month, billed annually. Educators can get a group subscription for free.
Including videos and exercises, this course lasts about two hours.
This course has no prerequisites.
Google Cloud’s Introduction to Generative AI Learning Path covers what generative AI and large language models are for beginners. Since it’s from Google, it provides some specific Google applications used to build generative AI: Google Tools and Vertex AI. It includes a section on responsible AI, inviting the learner to consider ethical practices around the generative AI they may go on to create. Completing this learning path will award the Prompt Design in Vertex AI skill badge.
Another option from Google Cloud is the Generative AI for Developers Learning Path.
This course is free.
The path technically contains 8 hours and 30 minutes of content, but some of that content is quizzes. The time it takes for each individual to complete the path may vary.
The path has no prerequisites.
Since this course is taught by an IBM professional, it is likely to include contemporary, real-world insight into how generative AI and machine learning are used today. It is an eight-hour course that covers a wide range of topics around artificial intelligence, including ethical concerns. Introduction to Artificial Intelligence includes quizzes and can contribute to career certificates in a variety of programs from Coursera.
Free if completed within the 7-day Coursera free trial, or $49-$79 per month afterward, depending on the course and plan. Financial aid is available.
Coursera estimates this course will take about eight hours.
There are no prerequisites for this course.
AWS offers a lot of AI-related courses and programs, but we chose this one because it combines fundamentals — the first two courses in the developer kit — with hands-on knowledge and training on specific AWS products. This could be very practical for someone whose organization already works with multiple AWS products but wants to expand into more generative AI products and services. This online, self-guided kit includes hands-on labs and AWS Jam challenges, which are gamified and AI-powered experiences.
The AWS Generative AI Developer Kit is part of the AWS Skill Builder subscription. AWS Skill Builder is accessible with a 7-day trial, after which it costs $29 per month or $449 per year.
The courses take 16 hours and 30 minutes to complete.
This course is appropriate for professionals who have not worked with generative AI before, but it would help to have worked within the AWS ecosystem. In particular, Amazon Bedrock is discussed at such a level that it would be beneficial to have completed the course AWS Technical Essentials or have comparable real-world experience.
Harvard’s online professional certificate combines the venerable university’s Introduction to Computer Science course with another course tailored to careers in AI: Introduction to Artificial Intelligence with Python. This certification is suitable for people who want to become software developers with a focus on AI. This course is self-paced, and students will receive pre-recorded instruction from Harvard University faculty.
Both courses together cost $466.20 as of the time of writing; this is a discounted price from the usual $518. Learners can take both courses in the certification for free, but the certification itself requires a fee.
These courses are self paced, but the estimated time for completion is five months at 7-22 hours per week.
There are no prerequisites required, although a high-school level of experience with programming basics would likely provide a solid foundation. The Introduction to Computer Science course covers algorithms and programming in C, Python, SQL and JavaScript, as well as CSS and HTML.
“MIT has played a leading role in the rise of AI and the new category of jobs it is creating across the world economy,” the description of the program states, summing up the educational legacy behind this course. MIT’s AI and machine learning certification course for professionals is taught by MIT faculty who are working at the cutting edge of the field.
This certification program is comparable to a traditional college course, and that level of commitment is reflected in the price.
If a learner completes at least 16 days of qualifying courses, they will be eligible to receive the certificate. Courses are typically taught June, July and August online or on MIT’s campus.
There is an application fee of $325. The two mandatory courses are:
The remaining required 11 days can be composed of elective classes, which last between two and five days each and cost between $2,500 and $4,700 each.
16 days.
The Professional Certificate Program in Machine Learning & Artificial Intelligence is designed for technical professionals with at least three years of experience in computer science, statistics, physics or electrical engineering. In particular, MIT recommends this program for anyone whose work intersects with data analysis or for managers who need to learn more about predictive modeling.
Completion of the academically rigorous Stanford Artificial Intelligence Professional Program will result in a certification. This program is suitable for professionals who want to learn how to build AI models from scratch and then fine-tune them for their businesses. In addition, it helps professionals understand research results and conduct their own research on AI. This program offers 1 to 1 time with professionals in the industry and some flexibility — learners can take all eight courses in the program or choose individual courses.
The individual courses are:
The Stanford Artificial Intelligence Professional Program costs $1,750 per course. Learners who complete three courses will earn a certificate.
Each course lasts 10 weeks at 10 to 15 hours per week. Courses are held on set dates.
Interested professionals can submit an application; applicants are asked to prove competence in the following areas:
Udacity’s Artificial Intelligence Nanodegree program equips graduates with practical knowledge about how to solve mathematical problems using artificial intelligence. This class isn’t about generative AI models; instead, it teaches the underpinnings of traditional search algorithms, probabilistic graphical models, and planning and scheduling systems. Learners who complete this course will gain experience in working with the types of algorithms used in the real world for:
This course costs $249 per month paid monthly or $846 for the first four months of the subscription, after which it will cost $249 per month.
This course lasts about three months.
Learners in this course should have a background in programming and mathematics. The following skills are recommended:
Whether it is worth taking an AI course depends on many factors: the course, the individual and the job market. For instance, getting an AI-focused certification might contribute to getting a salary increase or making a career change. AI courses could help someone learn AI skills that might be a good fit for their abilities, or could be the first step toward a lucrative and life-long career. Educating oneself in a contemporary topic can always have some benefits in terms of practicing new skills.
Some introductory AI courses do not require coding; however, AI is a relatively complex topic in computing, and practitioners will need some programming skills as they progress to more advanced courses and learn how to build and deploy AI models. Most likely, intermediate learners need to be comfortable working in Python.
SEE: Help your business by becoming your own IT expert. (TechRepublic Academy)
Some of these courses and certifications include education in basic programming and computer science. More advanced courses and certifications will require learners to already have a college-level knowledge of calculus, linear algebra, probability and statistics, as well as coding.
