Skip to main content

Indianapolis Campus

Indianapolis Main Campus Satellite Locations

Introduction to AI

This introductory course provides a comprehensive foundation in Artificial Intelligence (AI), empowering students to work confidently with AI tools, systems, and methodologies across diverse professional settings. They will explore the scope and key disciplines of AI, including data strategies, model architectures, and the complete AI lifecycle. Through activities, students will apply prompt engineering techniques to enhance content generation, data analysis, and problem-solving. They will also integrate responsible AI principles into their work and be equipped to analyze the societal and workforce impacts of AI technologies across different contexts. By engaging with real-world scenarios and applied projects, students will learn to design, assess, and adapt AI solutions that are effective, fair, and sustainable.

  1. Define, differentiate, and contextualize foundational AI concepts, paradigms, and models.

  2. Evaluate AI-ready data strategies by assessing structured and unstructured datasets, applying data quality enhancement techniques, and implementing governance principles.

  3. Explain and illustrate the complete lifecycle of AI systems from data acquisition and preparation through training, evaluation, fine-tuning, deployment, and inference.

  4. Develop and implement effective prompt engineering strategies to optimize interactions with generative AI tools for tasks such as content generation, data analysis, and problem-solving.

  5. Select, adapt, and justify the use of AI models, architectures, and tools based on application requirements, interpretability needs, scalability, infrastructure constraints, and integration considerations.

  6. Assess the performance, limitations, and risks of AI systems, and implement mitigation strategies for threats using guardrails, retrieval-augmented generation, and defensive architectures.

  7. Integrate responsible AI principles into all stages of AI development and ensure compliance with relevant legal, regulatory, and governance frameworks.

  8. Analyze societal, workforce, and environmental impacts of AI, and synthesize and forecast emerging trends to anticipate opportunities and challenges.

Course Content

Topical areas of study include:

  • Foundations of Artificial Intelligence

  • Data Strategy for AI

  • AI Model Architectures and Ecosystem

  • AI Model Lifecycle and Deployment

  • Prompt Engineering

  • AI Reliability, Security, and Risk Mitigation

  • AI Ethics, Governance, and Responsible AI

  • Applications, Infrastructure, and Societal Impact

This course is offered as a virtual, synchronous program. That means there are scheduled online lectures and interactive workshops. The course meeting will be bi-weekly in a virtual setting via Zoom.

Familiarity with basic programming concepts and data analysis is beneficial but not mandatory.

The Introduction to Artificial Intelligence course is intended to help learners apply AI knowledge within their existing or future professions. By developing skills in data strategy, prompt engineering, responsible AI, and practical tool use, participants can enhance their effectiveness in fields like business, education, healthcare, manufacturing, and IT. This training positions them to integrate AI innovatively and productively into their work, making them more adaptable and competitive in an AI-driven world.

Also Offered in Indianapolis