Learning for Advanced Learners: Making the Effort for AI/GenAI

Here in the biotech world, we do get training at least to understand some of the popular issues, such as Cybersecurity, AI and GenAI. We use some of the tools related to these topics and we support the groups that create new methods and make policies for these areas.

That makes it that much more difficult to find courses that don't merely reinforce what we know but also add to it. For many of us, training becomes a personalized effort.

What I mean is this: in biotech, of course we know that whether we are an employee or consultant, when we begin a new job or customer, we will go through the multitude of basic trainings to show that we attended and often also passed certain key courses. For those of us who have any amount of GxP work, that coursework is significantly increased.

Yet, we are expected to grow and some of us do actively want to be those lifelong learners. Next, we go on a search for the right coursework and areas where it will make an impact. That coursework needs to feel justified in the time we spend and the cost. Most of us will not be able to justify the cost or time required to add yet another college degree, for example.

A few years ago, I took a series of AI and of Cybersecurity courses here in LinkedIn just to show I was sincere about staying up-to-date on the topics. Since the most recent shift with GenAI, despite any training we get at work, I had wanted to find a more complete update course to show how everything ties together.

Finally, I Found Something

Some of the companies out there are actively training us on enough AI and GenAI to boost our productivity, not necessarily to replace us. So, we do use it to varying extents.

I didn't want a set of courses that completely duplicated the courses we tend to get at work, but I found this and now have the certificate to show that I did attend the six courses in the plan and passed all the quizzes and tests:

IBM Certificate for 6-Course plan on AI/GenAI

Criteria

These were my basic criteria to finding the right coursework and, now that I've finished this, feel satisfied with this choice. I am going to give these thoughts to you not for you to duplicate this, but to get you thinking about your own training goals:

• Should not be extremely long: Each of these courses in the plan were estimated at less than 2 hours to achieve and the entire plan at approximately 10 hours. It took me somewhat less time as I did already understand many of the concepts.
• Should refresh what I already know: It did a better job than I realized as I didn't realize how many pieces of history I'd forgotten, for starters. On a daily basis, we focus more on the hands-on examples less on the history and the historic pieces tend to fade from memory.
• Must build onto what I already know: The course refreshed my memory on some of the computational methods I used to use and built on that. That made it clear to me how the advancement took place and made me see how my own experience fit into the picture. Beyond that, it gave some useful examples that I won't typically have an opportunity to use at work but which made the later technologies and issues stand out more clearly.
• Higher level information rather than extreme details: I'm not looking for a new degree but to use the latest tools, support the people creating new computational methods, and be able to lead efforts that involve these technologies.

Other Issues to Consider

Here are a few items that worked well that I wasn't specifically looking for:

• A little on the technical side: It was easy for me to understand the programming terms the course used and it helped me understand how all the pieces of this are linked. They were not so prolific and deep that someone who was not a programmer couldn't grasp them but might take a little more time.
• Included an Ethics module: We talk about ethics at work, but usually more broadly. Thus, getting an entire module that just covers the greater details of this and for just this topic is not that easy to find. In fact, I considered taking this module all on its own. In any case, it gave great examples how to look a some of these issues and address them.
• An opportunity to create and watch a real-life example: I thought it was fun to run through a real example with the Watson dashboard as the background. You do not get a real-time use of that tool, but enough screenshots and instructions to manage the example that it is a better activity than merely reading about it. In addition, if you use other tools with modern dashboards of cloud services, such as MS Azure or AWS, a lot of the concepts in there will look and sound familiar.

Note: Not that I have had the occasion to need to know much about chatbots at work, but learning more details behind how best to use them was kind of fun information to have at-hand when I next got stuck using one to get support for myself.

Finally

With our biotech world in IT and science moving ahead so quickly, like many others out there, I feel the pressure to remain relevant. No matter what my past track record, I am convinced that it will not guarantee my future.

With the job and consulting market so competitive, each of us who are looking to prove that we are not falling behind and are interested in remaining on top of the issues find we have to run faster and faster to do that.

As much as we talk about the importance of "soft skills," notice how many people in leadership claim that they're a "great" communicator. So many that it makes us skeptical to see it so often. In effect, that doesn't make us stand out. A mixture of showing our skills and also a willingness to grow seems to help.

Again, my goal is not to claim to be the expert in anything at all. I want to reiterate that positions in leadership, as business partners - all these require not that we claim we can take the place of the people who are at the bench creating scientific methods or working directly with neural networks. But we do have to understand what they're doing well-enough to be able to have a conversation with them and bring that information to others in the organization.

Note: Too bad it is now not as easy as taking the next course from the same place. The learning platform suggested a course on ChatGPT prompt engineering but, in looking at the details, that course really does look completely like the training we already get at work except that it is not a music playlist we learn to create at work as this course will have you do.