Avoiding Automation
According to Goldman Sachs as many as 300 million jobs around the world could face automation in some way. Most of these are white collar office jobs that artificial intelligence could replace. So what can you do to avoid automation eliminating your role? The answer is you learn how to use artificial intelligence and machine learning to your advantage. You develop skills that will be relevant in a future workforce.
I’m going to share with you the top five online courses in artificial intelligence and machine learning that you can take today to help you skill up. I’ll cover it in the following way. I am talk about the time commitment and the format. I’ll explain whether it’s 100% self-paced or if it’s based on cohorts where you start and finish with a group of other students on a specific timeline. I talk about cost and also what you’ll learn. I’ll go in order starting with the most beginner friendly and most cost effective. All the courses that I’ll talk about today will be in the links provided down below.
AI Foundations for Everyone
Course Format and Cost
Course number one is AI Foundations for Everyone. IBM offers this through the Coursera platform. Time commitment’s about 1 month at 10 hours a week, so not very long. Format is entirely self-paced and cost is about $39 a month.
Through Coursera you do have the option to audit some of the content for free. You can test it out before you actually pay for it if that’s the route you want to go. But if you want to earn the certificate there is a cost associated with that. Now this course program is about as beginner friendly as it gets. It really just gives you an overview of artificial intelligence. It shows how organizations apply it in different industries and in different use cases. All of it’s useful if you’re starting with no knowledge at all in AI.
Learning Generative AI Tools
There’s really no programming involved. The focus here is on being able to use some of the generative AI tools that exist for text, image, audio and video generation. You’ll get a good sense for what it’s capable of today. You’ll learn how it might be able to improve your productivity.
There’s also good content here on prompt engineering. This is just the way in which you phrase something to AI in order to get the desired output. Generally speaking the more detailed and specific you are the better the output. Whenever you use generative AI tools like ChatGPT, Microsoft’s Copilot, or Google’s Gemini you can get better results.
AI for Business
Building No Code Models
Course number two is AI for Business by the University of Pennsylvania. It’s also offered through the Coursera platform. Time commitment is also about a month at 10 hours a week. It’s also entirely self-paced. The cost is a little bit higher at $79 a month.
This is another solid course, also pretty beginner friendly. But it does go into more detailed explanations about the different AI and ML models that organizations commonly use. There’s also some content on how you can build your own models through no code platforms. If you don’t have any programming experience nor do you really want to learn, you actually have the option here to apply what you’ve learned conceptually. You can still build something useful.
There’s also content on how organizations apply AI to different industries. It goes into marketing, finance, and management. Then it concludes with AI strategy and governance. You’ll learn how to use it responsibly and how to roll this out to an organization.
Machine Learning by DeepLearning.AI
Expert Instruction from Andrew Ng
Course number three is machine learning by deeplearning.ai. Time commitment is about 2 months of around 10 hours a week. Format is self-paced. Cost is around $49 a month.
Andrew Ng designed this course. He’s actually one of the founders of Coursera but he also happens to be one of the world’s foremost experts on AI and ML. He is a professor at Stanford University. He was the director of Stanford’s AI lab. He’s also the founder of deeplearning.ai which is a series of online courses on artificial intelligence. His influence even extends into the corporate world. Most of his efforts have been spearheading the democratization of AI and ML.
Supervised and Unsupervised Learning
This course covers the foundational elements of machine learning. It starts with supervised machine learning with regression and classification. Then it covers more advanced topics like decision trees and ensemble methods. It’ll end with unsupervised machine learning that covers topics like clustering and anomaly detection.
The good news is this course is entirely self-paced. If you need to take a break you can. You don’t need to finish it in 2 months although the sooner you finish it the less you have to pay. But the content can be a little bit complex if you’re just seeing it for the first time.
That’s good because the next two programs are a little bit more expensive. If those are out of your budget this one is just a fraction of the cost. The course curriculum here is very robust. There’s plenty of content as well as programming assignments. You still get relevant practice in building these algorithms.
University of Texas Postgraduate Program
Comparing Professional and Master’s Programs
Course number four is the University of Texas postgraduate program in AI and ML. Time commitment is quite a bit longer. It’s 7 months of around 10 hours a week. Format is cohort based. You start with a group of people and you end with that same group. Cost is around $4,200 but I’ve seen that price fluctuate a little bit from time to time.
University of Texas is one of the leading universities in the field of artificial intelligence. In fact they recently launched a full-fledged master degree program in artificial intelligence. Although that is quite affordable for a degree program I won’t go into that one. That is quite a bit more of a time commitment and it’s substantially more challenging.
Mastering Python and Business Use Cases
I wouldn’t say it’s beginner friendly at all. Whereas this postgraduate program is great for anyone that doesn’t have any kind of programming background. It’s also great for anyone without any kind of background in computer science or coding. While this is great for beginners because it teaches you all the coding steps, the difficulty and time commitment is quite a bit more. It’s more than what you would find in some of the Coursera courses that I mentioned earlier.
As far as content goes it starts by giving you a really solid foundation in Python. It’s one of the most popular programming languages in the world especially for data science. You’ll learn how to code here and use Python for data analysis. Then it takes you through some of the more common machine learning algorithms. You’ll learn about regression, decision trees, clustering, and random forests among many others. You’ll also learn what the business use cases are for each of those algorithms.
Real World Applications and Personal Experience
Lastly the program goes into artificial intelligence and deep learning. It covers taking unstructured data like text, image, and video, learning from that and then making predictions. This is what goes into ChatGPT and other language learning models. It’s what you see with image generation in midjourney or video generation with Sora.
If you want to take this into the real world, the company that I think is doing the best job at it is Tesla with their self-driving car technology. Although it’s highly complex. By the way this program is one that I’m currently in. I’ve got a whole other series where I’m documenting my experience doing basically a real-time review. Make sure to check that out if you want to learn a little bit more about that.
Berkeley Professional Certificate
Statistics and Data Science Libraries
Course number five is the Berkeley professional certificate in AI and ML. Time commitment is around 6 months of around 10 to 20 hours a week. Format is cohort based. Cost is around close to $7,000. Berkeley is one of the top schools for computer science. Getting any kind of credential from this university is going to be beneficial.
The structure looks very similar to the University of Texas program. That looks to be fairly beginner friendly. It starts with foundation in statistics and data analysis. It looks like Python is used here exclusively along with all the relevant data science libraries like Pandas and Seaborn. Then it goes into common machine learning algorithms. It ends with artificial intelligence and deep learning just like University of Texas.
Structurally pretty similar. It appears to cover mostly the same concepts in approximately the same order. Between this one and the last one if you’re deciding between the two I think it really just depends on your budget. It also depends on the desire to have one school over the other on your resume.
Staying Competitive in the Job Market
While I believe it to be very important to get up to speed on how AI and ML is going to transform the job market, it’s not the only way to stay competitive. Depending on where you want your career to go there are many more affordable online learning options out there. Make sure to check out my other video where I talk about a platform called course careers. It’s one of the easiest and most cost-effective ways to pivot your career into a high demand job field.