Artificial Intelligence Certification at WGU

Careers in Artificial Intelligence  

Few fields are evolving as quickly as artificial intelligence. From generative AI programs that facilitate the discovery of new medications to AI-supported online banking, the potential applications of AI are endless. Individuals interested in AI certificates have diverse career options to pursue. Here are some of the top AI jobs currently creating a buzz in the industry:

What Does a Robotics Engineer Do?  

One of AI’s most valuable features is its ability to automate tasks and free human workers to focus on more complex and higher-level responsibilities. Robotics engineers are leaders in AI-enabled automation. These professionals plan, develop, and maintain custom robotics systems that increase productivity, streamline processes, and reduce costs. Their daily responsibilities vary, but robotics engineers typically handle the following tasks:

• Collaborating with stakeholders to identify potential robotics applications.
• Determining the scope and timeline for new robotics projects. 
• Designing and building prototypes. 
• Testing robotic systems to discover defects or areas for improvement. 
• Overseeing construction and maintaining documentation of the development process. 
• Performing maintenance and installing updates to robotics systems as needed. 

What Does an AI Consultant Do? 

Many organizational leaders recognize AI's value but are unsure how to integrate artificial solutions. This is where an AI consultant can help. By evaluating a business’s needs and goals, AI consultants can pinpoint ways that AI can improve operations, reduce expenses, and enhance outcomes. Some AI consultants work for consulting firms, while others are independent contractors who execute consulting jobs on a freelance basis. Some typical job duties of an AI consultant include: 

• Meeting with executives, department heads, project managers, IT professionals, and other stakeholders to understand the organization’s needs. 
• Evaluating the organization’s technological capabilities, budgetary requirements, workflows, and processes.
• Identifying potential applications for AI.
• Choosing AI tools that can seamlessly integrate with the existing infrastructure. 
• Overseeing the implementation of AI solutions.
• Providing ongoing training and support to employees and business leaders as they learn to work with AI technologies. 
• Ensuring organizations recognize the ethical and regulatory concerns associated with artificial intelligence and know how to navigate these issues efficiently. 

What Does a Business Intelligence Analyst Do?  

Business intelligence analysts evaluate data, forecast trends, and help businesses make strategic decisions. These professionals frequently use AI to make sense of massive, unstructured data sets. Integrating AI technology into business intelligence solutions helps analysts detect inconsistencies, manage risks, optimize processes, find new opportunities for business growth, and gain other actionable insights.  On a typical day, a business intelligence analyst handles the following responsibilities:

• Gathering detailed information about the business’s short- and long-term objectives.
• Analyzing sales data, customer metrics, market trends, and other forms of data.
• Using data visualization tools like Tableau and Power BI to organize and distill complex information into easy-to-understand formats.
• Identifying data-driven strategies for improving outcomes and achieving business objectives. 
• Presenting findings and recommendations to business leaders. 

What Does a Prompt Engineer Do?

Whether an AI tool generates text, analyzes images, translates languages, or automates tasks, it’s only as accurate as the information that’s fed into the system. Prompt engineering is the process of training an AI model to provide reliable, accurate information. By optimizing the input data, or prompts, that AI programs rely on, prompt engineers improve the system’s outputs and enhance the user experience. Some of a prompt engineer’s job duties include: 

• Using a combination of trial and error and creativity to design prompts that yield the most accurate, meaningful responses from AI programs.
• Constructing prompt libraries and guides to help users make the most of AI models.
• Fine-tuning AI models to enhance their performance and reliability. 
• Collaborating with data scientists, IT professionals, and other stakeholders to identify ways to enhance AI model results.
• Ensuring AI models adhere to privacy laws, regulations, and ethical guidelines.