Learn how to harness the power of artificial intelligence to transform your workflow with hands-on training in ChatGPT and Microsoft Copilot. This course will teach you how to generate content, streamline tasks, and integrate AI into business communication, writing, analysis, and productivity tools.
Harness the creative power of AI with this hands-on workshop. Explore the cutting-edge world of artificial intelligence and learn how to generate text, ideas, and more with the innovative technology of ChatGPT.
Leverage the power of cutting-edge AI tools and features in Photoshop, Illustrator, InDesign, and other Adobe apps in this hands-on class.
Learn how to use generative AI to improve your video and motion projects. Create visual and audio assets, integrate AI tools into your daily workflow, and learn how copyright and data confidentiality work when using AI content.
Learn how to incorporate AI in your marketing strategy with this in-depth course. Explore how to use AI-driven tools to help your SEO, SEM, social media marketing, analytics tracking, paid advertising, and more.
Master AI technologies for business, marketing, design, data analytics, and more in this cutting-edge certificate program. In this program, you'll learn how to optimize Excel workflows, create stunning video content, create captivating graphics, analyze data efficiently, boost workplace productivity, and more with the power of generative AI.
Learn Python, SQL, automation, and machine learning to become a Data Scientist. Gain Python programming, data analysis, SQL querying, and predictive modeling skills. Perfect for beginners, this program prepares you for entry-level data science and Python engineering roles. Unlock high-paying job opportunities in the field of data science.
Gain practical skills in analyzing datasets, building predictive models, and creating AI-powered applications using Python and industry-leading tools.
Create, style, and enhance web apps with AI capabilities. In this advanced Python course, you'll develop a powerful sentiment analysis web application with Flask and the OpenAI API integration and learn how to take your coding projects to the next level with AI.
AI stands for Artificial Intelligence, a term that may well conjure up images of Asimovian robots or science fiction film stars Robby the Robot from Forbidden Planet and the computer-gone-amok HAL from 2001: A Space Odyssey. Contemporary artificial intelligence systems resemble HAL more than Robby in that they’re inside your computer rather than being clunkily moving humanoid metallic structures. Like Star Wars icon C-3PO, Robby the Robot was a suit an actor wore, although moving robots have existed since the 1960s and earlier, not least in the form of the audio-animatronic (AA) figures that appear in several Disney theme park attractions, including the zany singing birds and orchids in the Enchanted Tiki Room and the full-size humanoid protagonist of Great Moments with Mr. Lincoln.
Putting aside those simulations of artificial intelligence, the real artificial thing—computers that seem to think for themselves—has been around since the days of Robby the Robot. Alan Turing, the Computer Scientist and mathematician who is considered the father of AI, employed the term machine intelligence to describe the process of creating a computer possessing some form of intelligence that is comparable to the human kind.
Computers were beating humans at chess in the 1990s, and, in the early 2000s, humans began regularly interacting with comparatively primitive artificial intelligence systems when speaking to disembodied voices on the telephone or when employing such now-everyday things as search engines or the recommendation algorithms that are part and parcel of using everything from Amazon to YouTube. In the 2020s, AI has become a brave new commonplace thanks to the advent of so-called Generative AI, in which computers are able to “create” text, images, videos, and audio in response to everyday human language commands.
Platforms such as ChatGPT, Adobe Firefly, and Udio can perform truly remarkable tasks and have already proven to be game-changers across the business world. That may seem scary, but AI, however unregulated and ahead of itself ethically it may be, is here to stay. There’s no sense in pretending it doesn’t exist; the future is going to smile upon people who know how to make AI work for them.
Many people probably think that ChatGPT is there so eighth graders can get the computer to write their book reports on Animal Farm so they don’t have to tear themselves away from their video games to read Orwell’s very short novel. There are efforts underway to watermark AI-generated text, but, ironically, neither AI nor eighth-grade teachers are infallible when it comes to detecting AI-generated text. While ChatGPT can, indeed, write papers on Orwell, that’s underestimating its capabilities while making ethically questionable use of the platform. ChatGPT can be used to perform a world of useful and ethical business functions.
One much-suggested use of ChatGPT today is to get your creative juices flowing. You can ask it to give you the first three pages of the Great American Novel. Music-generating bots can compose the first thirty seconds of your next symphony. And image-generating AI can spit out an image you can subsequently tweak into the next De Sterrennacht.
That’s still only the tip of the iceberg, however. AI is perhaps at its most useful when used to automate wearisome tasks. You can have it choose an outfit, perform cost estimates, or even cast your community theater’s production of Entertaining Mr. Sloane. You can go through and correct an AI model’s decisions, and even get it to refine its choices in light of any additional parameters you may feed it. In many ways, AI is like a computer you can program in plain English (or French, Marathi, Malay, or even Albanian).
Getting AI to do your bidding is a function of how well you tell it what you need it to do. These commands are known in the AI world as prompts, and much of your AI class will be devoted to the crafting of these all-important directives. You can still give ChatGPT a prompt like “Write three paragraphs about Orwell’s Animal Farm.” That will get you three generic paragraphs about Snowball, Napoleon, and Boxer that any eighth-grade teacher should be able to see through. You’ll do better with “write three paragraphs about Orwell’s Animal Farm in the style of an eighth grader, including two spelling mistakes and omitting all mention of the Russian Revolution.”
That’s not to say that the point of an adult AI class is to learn to use generative AI without getting caught. There’s so much more that it can do. In fact, its “creative” capabilities are just those of an exceptionally well-trained parrot. All ChatGPT does is follow one word with what it has learned to be the most likely next word. The term for this—though ChatGPT will deny being one if you ask it—is a stochastic parrot. You’ll very likely have forgotten about the creative uses of AI by the time you’ve finished a serious AI course.
This is the number one skill required to operate AI, and it’s not as easy as you might think it is. While AI is, in a manner of speaking, intelligent, it’s not a very good mind-reader and needs to be told what to do in terms it can understand. As a rule, the more specific you are, the better your results will be. Certain commands are more effective than others, and you can use prompts to train the AI model further. Thus, for example, “you’re an American eighth grader and a good, not great, student whose spelling is shaky; write three paragraphs about Orwell’s Animal Farm without mentioning the Russian Revolution, but stressing the importance of the character of Boxer” will get you your best version of your digital book report yet. What you put into the model is directly proportional to what you get back, which harkens back to the old computer adage GIGO: garbage in, garbage out.
As the buzz around generative AI today might suggest, the technology is good for more than writing book reports. It can also be used to accomplish dreary, dull, daily tasks, assuming you know how to get what you want out of it. You can, for instance, have an AI model create an entire exercise program for yourself and continually refine it to account for an injury or other changes. You can even design the GPT (the initials stand for generative pre-trained transformer) so that you can input reps and weights as you work through the program. Or, if you’d rather eat than exercise, you can have the GPT write out a shopping list based on recipes you feed into the machine. And, of course, office tasks can be automated by the same means, so that time cards, meeting notes, and cost estimates can become significantly fewer onerous.
Adobe’s Firefly makes a delightful toy. How can you resist something that can generate an image of three quokkas in pajamas eating a picnic breakfast on the field at Minute Maid Park during a game between the Astros and the Rangers with such adorable results? Amusing though that may be (and it is amusing), now imagine that you work for the advertising agency that represents a famous doughnut chain as it seeks to introduce its new mascot, Quispy the Quokka. Tweak your fun prompt, and you’ve suddenly got a useful advertising image you can (because it’s Adobe and it all goes together) edit using Photoshop or Illustrator into something that is sure to increase doughnut sales.
Machine learning, a form of AI, plays a central role in data science, where it’s used to automate and speed up repetitive tasks like data cleaning. You can also apply AI techniques on a somewhat less grand scale by using it to accelerate the more tedious tasks spreadsheets involve. AI can handle the manipulation, visualization, and analysis of data of all sorts, especially in cases of reports that need to be generated on a regular basis. You can hand the chatbot the new week’s doughnut data and it will come up with a chart that will illustrate the meteoric success of Quispy the Quokka.
GIGO, garbage in, garbage out, means that computers function much better when they’re given the right kind of input. When you’re coding in a computer language, the syntax of the language dictates the tone you're adopting when you’re issuing commands. With artificial intelligence and natural language processing, you’re issuing your commands in English or Albanian, which need to be succinct, clear, and unequivocal. Practicing putting your thoughts into terms that possess these virtues is unquestionably going to rub off on your use of language in general. You’ll get better at asking for exactly what you want and become aware of the nuances in what you’re saying. While AI can write for you, working with it will make you into a better writer.
Most of the generative platforms are designed so that, well, a lazy eighth grader can operate them. Not well, not efficiently, and with generic results at best, but, if you can type in one of ChatGPT’s 95 languages, you can get generative AI to do something for you. This is the level of “write three paragraphs about Animal Farm” prompt that returns output about agribusiness. Assuming you’re smarter than a lazy eighth grader, you’ll be able to do more than that right away, although the temptation to use AI without having gone into the matter in depth is tempting, but it may leave you in a GIGO scenario. To get something actually useful out of an AI model requires some study, since you can easily waste a lot of time writing clumsy prompts. That said, you can pick up the essentials of good prompt engineering in a few days. Mastery will take more time: when it comes to writing AI prompts, practice does indeed make perfect.
Probably the hardest part of learning to use AI is that it requires a great deal of patience to get your prompts just so. There’s a lot of trial and error at the beginning. As ChatGPT has usage limits, you can’t keep dashing off ineffective prompts at a rate of a hundred per hour. You need to think twice before pushing the arrow button. Once you have the knack, it’s really pretty easy to get generative AI to generate what you need, but developing the knack may prove severely frustrating.
You can get that generic Animal Farm book report that will get you in trouble with your teacher—in under ten seconds. To create a GPT model that will manage time cards for your office staff or cast your next Joe Orton production—you’ll need to be able to give the model elaborate instructions, and learning how to do that will, indeed, take longer than ten seconds. Two weeks of full-time study should put you firmly on your way, but that does mean putting quite a bit of work into it. You’re going to be treading on terra incognita, and you don’t want to rush the process, lest you end up with that report on animal husbandry rather than Orwell’s novel.
There are roughly three ways of learning a new skill these days. You can study synchronously in-person or online, or you can study asynchronously online. Synchronous is a fifty-cent word that means you and your instructor are working in the same moment in time and can communicate with each other. You can thus ask questions when you don’t understand something, and you can receive responses in real time. Asynchronous is the opposite of that: you’ll be learning from canned video presentations that allow for no interaction between yourself and the teacher—at least until they figure out time travel.
A synchronous class can unfold in one of two ways. You can either commute to a little red schoolhouse or connect to a virtual classroom. The first method hardly needs an introduction, as going to school to learn is the way you learned to learn starting in kindergarten. The second is a more recent development, although it already dates back a couple of decades to the early days of public acceptance of the internet. True, you’re not inhaling the same oxygen as the instructor, but, on the other hand, you’ll be in your own space and much more able to look after your own comfort as you learn. In these circumstances, the dog can be a distraction, but many have come to prefer periodically shushing the family hound to commuting to a brick-and-mortar school. And, as live, in-person IT classes are about as rare as a 125°F steak, you may end up taking advantage of the far larger selection of live online courses.
Asynchronous classes are as abundant as asparagus in May, but this type of class comes with the enormous drawback of providing no contact with the instructor. The resulting impossibility of asking questions can prove extremely frustrating, to say the least. AI being a rapidly evolving field, the instructional videos on the topic that were recorded as recently as a year ago are already seriously out of date. All that said, if you can’t work a live class into your schedule, you may have no other option than an on-demand course for learning AI. You’ll certainly be able to learn something about the topic from one of these on-demand classes, but there’s no disputing the fact that you’ll be able to learn more from a live class.
YouTube is chockablock with AI tutorial videos, all of which cost the same as admission to the Menil Collection. These videos operate on the same principle as asynchronous classes just described: you pull up the video and watch it passively, without being able to stop the teacher and ask a question when you don’t understand something. You’ll also be confronted with the problem of classes that have passed their expiration dates, as AI tutorials tend to age about as well as milk. You will learn a little bit about prompt engineering from these videos, particularly if you concentrate on those that are most recent, but, if you’re serious about using AI professionally, you’re going to need a paid, live class.
Perhaps the most useful skills you can learn to complement your AI training are the ones that make it possible to work with the AI outputs you receive. Thus, if you’re working with AI images from Adobe Firefly and you don’t like the pattern of the pajamas Firefly put on your breakfasting quokkas, you can very easily use Photoshop to change it. Although it could well be a skill you already possess, knowing how to use Word is going to come in extremely handy when it comes to editing the text that ChatGPT produces for you. You can continue on down the line with audio and video software as well, depending on what you want to achieve with the platform you plan to use. You shouldn’t consider what comes out of AI as a finished product; you should be prepared at least to tinker with it, which, in turn, means knowing how to use software that allows you to do so.
AI is rapidly invading every corner of the American industrial landscape. Fields central to Houston’s economy—including healthcare, aerospace, and finance—are either already availing themselves of or are ready to avail themselves of the possibilities inherent in generative AI. Moreover, Houston is an evolving tech hub that includes companies that develop AI applications for other companies. And, although they hardly have the largest budgets for bringing in AI, not-for-profit organizations that depend on fundraising can gain a lot from generative AI as well.
Among the industries that use AI, there can be no question that the most preeminent of them is AI itself, i.e., companies that develop AI and use it to create solutions for other companies. The technology is advancing exponentially, and the Bayou City’s growing tech sector would hardly be complete without contributions to the advancement of AI and its application to other industries. The possibilities here are almost endless, whether for optimizing business workflows, the Internet of Things (IoT), blockchain, energy production, or data collection. That list barely scratches the surface but gives an idea of just how far-reaching AI development is in Texas's largest city.
Texas Medical Center is the largest such complex in the world, and over 11% of Houston's workforce is employed in the healthcare sector. Houston's hospitals and doctors are making ample use of Artificial Intelligence. It is used in a wide variety of ways, ranging from the mundane—such as transcribing patient records or notifying patients of upcoming appointments—to reading test results, proposing treatments, and predicting patient outcomes. Healthcare is one of the fields that has most fully embraced AI, which is poised to transform the industry almost beyond recognition.
Aerospace and aviation have long been mainstays of the Houston economy, and both are already making extensive use of AI. Predictive maintenance keeps planes in shipshape condition with no waste of time or manpower. AI is used for training flight crews, most effectively when its simulations are combined with virtual reality technology. It can also be employed by pilots while in the air: it can keep track of fuel levels, weather conditions, and the plane’s mechanical systems. Beyond that, AI, teamed with 3D printing, can help design more efficient aircraft. It is also being used to improve the dismal customer experiences that airlines seem doomed to continue offering: chatbots are getting better and better at holding conversations about important matters such as scheduling, and they can also provide customers with customized recommendations of vacation destinations and help customers find the most economical fares.
Thanks partly to its tax rate, Houston is one of the biggest financial centers in the country, and any financial organization worth its salt is likely to be using AI. AI has been used in the sector for a while (who doesn’t recall those highly unpleasant encounters with banking chatbots as recently as five years ago?), but the advent of generative AI is rapidly transforming the picture. Since AI can assimilate huge amounts of data, it can be used to make more precise recommendations with regard to loan approvals in a way not previously imagined by bank officers. Similarly, a chatbot can be developed to offer investment advice, and another can be designed to speed document verification and KYC (know your customer) protocols. In the insurance field, generative AI can be used for underwriting and even to facilitate claims resolution.
AI is by no means exclusively the province of greedy corporate barons. Not-for-profit organizations are harnessing the new technology as well, from automating repetitive tasks such as keeping donor lists up-to-date to predicting fundraising outcomes through the use of both propensity and predictive models. AI enables organizations to target not just certain groups, but rather individual donors, and can assess who might make a donation and when. Similarly, generative AI can tailor fundraising materials to individual donors. Everything from accounts payable to social media management can be automated through generative AI, streamlining operations (a desperately necessary factor in not-for-profit organizations)—and what’s even more important for a not-for-profit organization—maximizing fundraising receipts.
Although instruction in how to employ generative AI for the common good and individual gain started out a couple of steps behind the development of the technology, education has since caught up with the rapidly developing reality. If you decide you wish to take a class in this red-hot subject, you’ll find several possibilities at your disposal, though perhaps not as many as you might expect. You’ll still have a choice of synchronous and asynchronous classes, including one that you can attend in-person in the Houston area.
The Knowledge Academy offers its Introduction to Artificial Intelligence both in the Philip Johnson-designed Post Oak Central complex and online. While your virtual classroom at home may not have been designed by Philip Johnson, it’s still home. The course’s syllabus covers the basic principles of generative AI before delving more deeply into such topics as machine learning, the concept of rationality, fuzzy logic, and even an overview of robotics. There are no formal prerequisites, especially not the ability to code. An asynchronous version of the course is available, too.
Great Learning has a Generative AI for Business course, offered on a hybrid model of self-paced video lectures and live mentoring sessions, academic support, and a dedicated program manager assigned to each student. The curriculum begins by showing participants how to leverage generative AI for business purposes, then moves on to teaching Python and designing generative AI solutions using Microsoft’s Azure Open AI. An optional module allows students to prepare for the Microsoft AI-900 exam; the certificate awarded at the end of the course will come from Microsoft Azure. No technical background is required to register.
A much more involved program that does require technical knowledge is offered by the McCombs School of Business at the University of Texas at Austin in collaboration with ed tech company Great Learning. The curriculum covers Python for AI, deep learning with neural networks, natural language processing (NLP), recommendation systems, and supervised and unsupervised learning. The pedagogical model is again a hybrid of self-paced lectures and supervised projects, with the latter forming the foundation of students’ final portfolios. Personalized one-on-one career guidance is included in the form of mock interviews and resume and LinkedIn profile reviews.
Another famous university partnered with an experienced ed tech company is the collaboration between MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and Get Smarter, in the form of a short Artificial Intelligence course. This offering is another hybrid of on-demand learning with human supervision, adding a socially interactive dimension to what would otherwise be a self-paced course. The syllabus is devoted entirely to business applications of AI from the standpoints of machine learning, natural language processing, robotics, and the greater implications of AI in business and society.
If you're not a programmer and have no interest in the coding side of AI, and if you want a fully live class that allows for ample human interaction, you’ll find in Noble Desktop’s Generative AI Certificate a program that amply suits your requirements. It teaches immediately useful applications of the new technology, beginning with ChatGPT and then expanding into classes in AI for marketing, graphic design, video, and motion graphics. You’ll then continue to learn how AI can be used to simplify tasks in Excel, and finally for other data analytics purposes. No prior knowledge is required to join the course, which comes with a free retake (within a year) and recordings of all the classroom sessions to allow you to review material you may have missed the first time. Your instruction will be entirely live and online, meaning that you’ll be attending classes with a living, breathing, sentient, and helpful instructor who can answer questions along the way and guide you through a hands-on, learn-by-doing curriculum.
If the full Noble Desktop certificate program is more than you anticipate needing, each of the course’s modules is available separately. That means you can speedily get up to speed with the applications of AI to your particular field. All the benefits of the certificate program, including the retake option, are included with the individual courses. Everything is live and hands-on, with small class sizes and instructors experienced in these new technologies.
Few are the managers today who don’t wish their teams were adept at using AI. It’s today’s wave of the future, and AI competency is essential to staying current and competitive in just about any commercial venture. If you harbor these goals for your team members, Noble Desktop can well be just what you need. The school can arrange corporate training onsite at your premises or online, similar to the school’s regular classes, but tailored to your organization’s needs and the level of expertise your employees already have attained.
If you’d rather your team attend Noble’s regular classes, this is easily arranged with the school’s voucher program. Discounts are available for multiple purchases. Please do not hesitate to contact Noble’s corporate sales division for further particulars.