Artificial Intelligence (AI) Technologies

Our Artificial Intelligence (AI) Technologies curriculum is carefully structured to provide a background in the various facets of AI and their applications in current industries.

The curriculum typically begins with core courses that introduce students to the basics of machine learning, statistics of goal seeking, neural networks, deep learning, and generational transformers such as ChatGPT, which are the core technologies underpinning modern AI systems. 

Subject matter also includes a deep dive into using Artificial Intelligence (AI) technologies such as ChatGPT, Google Gemini and many other tools in your day-to-day job functions.  

Much of the core curriculum is dedicated to machine learning, where students become familiar with different training methods such as supervised, unsupervised, and reinforcement learning. Here, classic algorithms like regression, random forests, support vector machines, k-nearest neighbors, and neural networks are studied. Students also gain hands-on experience in implementing these algorithms in Python and its frameworks.

Data capture/handling is another critical aspect, as AI heavily relies on data. The curriculum covers data formats, preprocessing, feature extraction, and data visualization, teaching students how to work with large datasets, clean and organize data, and extract meaningful insights from it. 

Deep learning, a subset of machine learning, is given special focus. Students delve into the workings of neural networks, exploring various architectures like convolutional neural networks (CNNs) for image processing and recurrent neural networks (RNNs) for sequential data like text and speech. Natural Language Processing (NLP) and computer vision are also application areas covered in the curriculum.

The curriculum also addresses the ethical and societal implications of AI, including discussions on privacy, bias in AI algorithms, and the impact of AI on employment and society. This holistic approach ensures that students are not only skilled in AI technologies but also aware of their broader responsibilities as AI practitioners. 

Upon core completion, students are offered second tier (diploma level) courses and electives depending on individual goals and career center caps. These take two divergent paths, one with an emphasis on end use (pre-existing apps), and the other focused more on theory.  

Electives typically include AI applications in domains such as robotics, autonomous vehicles, medical machines, financial modeling, law enforcement (forensics), and manufacturing production. Towards the end of the program, students may engage in capstone projects or internships that provide practical experience in applying AI to real-world problems. 

Overall, our AI Technologies curriculum is designed to produce graduates who are well-versed in the theoretical and practical aspects of AI, equipped with the skills to develop and implement AI solutions across various industries. 

As an added benefit, if you are currently unemployed, you may qualify to have the entire program paid for, 100%, without any out-of-pocket costs to you. We are approved for WIOA, Trade Act, Section 30 and many other government grants.  We also offer various other financing options.  

Where to start? Our counselors are available to help put together a customized program to meet your needs.