Give
Artificial Intelligence (AI) certificates
Overview
Get the Artificial Intelligence (AI) skills you need to work in the digital economy.
Our two AI certificates, developed with the help of Intel Corporation, will be offered starting Fall Semester 2024. Through this coursework, you will:
- learn about the different types of AI
- use available tools
- discuss the ethical considerations of using AI
What is AI?
AI refers to the development of computer systems that can perform tasks that typically require human intelligence – things like learning, reasoning, problem-solving, understanding natural language and perception. These technologies are developed to improve performance over time without any programming.
Intel workforce partnership
Stark State is among a select group of community colleges across the country participating in Intel AI for Workforce Program, which aims to equip the workforce with the technical confidence, skillsets and competencies needed for jobs that utilize AI. The need for workers with these skills is expected to rise in the next few years.
Work in many areas, including
(may include, but not limited to):
- smartphone technology
- supply-chain automation
- fraud prevention
- energy supply and usage
- online shopping
- email spam filters
- diagnosing illnesses
Prepare for a career as a
(may include, but not limited to):
- marketing
- sales
- customer service
- finance
- research and development
Courses
Certificate options
AI certificates
Additional info
Program learning outcomes
- Describe what is and is not AI. Study the history of AI and its evolution over time
- Identify and analyze current trends in AI by correlating them with other technologies like IoT, Big Data and 5G.
- Identify three common domains of AI (Natural Language Processing, Computer Vision and Statistical Data) based on the type of underlying data.
- Examine and appreciate typical steps involved in an AI project through the AI project cycle.
- Discuss ethical concerns around AI and examine the societal impact it could have.
- Describe basic concepts and models encountered in machine learning and deep learning such as supervised learning, unsupervised learning, neural networks, reinforcement learning, etc.
- Classify different kinds of data available into structured and unstructured based on the underlying quality of the dataset. Appreciate the different roles each member of a typical data science team plays in a project.
- Examine common no-code tools available for AI project building and develop a use case using no-code tools in each domain of AI.
- Discuss and interpret the future of AI based on upcoming technological trends.
