AI
AI Essentials
This 4-hour course offers a well-rounded survey of Artificial Intelligence for relative newcomers to the field. It provides an overview of AI and Generative AI fundamentals, surveys public and open-source models, and explores multi-modal systems and prompt engineering. The course also examines AI applications in data analysis and visualization, and introduces other AI tools for image and media generation. The course combines lectures with demonstrations.
Duration
½ Day (4 hours)
Audience
Entry-level individuals with basic internet and Microsoft Office/Google Workspace skills who are looking to transition into AI-related roles or enhance their career prospects with AI knowledge.
Prerequisites
Basic proficiency in Internet navigation and Microsoft Office/Google Workspace. No prior AI knowledge is required.
By the end of this course, participants will be able to:
- Explain foundational concepts and historical milestones in AI, including the evolution from expert systems to generative AI and large language models (LLMs).
- Describe how chatbots and conversational AI systems function at a high level, and identify best practices for effective prompting and user interaction.
- Differentiate between general-purpose AI tools and embedded AI copilots, such as Microsoft 365 Copilot and Acrobat Assistant, and recognize how they support productivity in professional environments.
- Demonstrate how AI can enhance data analysis and visualization workflows, including interpreting trends, generating insights, and automating routine tasks using natural language interfaces.
- Identify major AI platforms, tools, and languages, including proprietary and open-source ecosystems (e.g., OpenAI, Azure AI, Hugging Face, Python, and Power Platform).
- Engage in informed discussions about real-world applications and limitations of AI, including ethical considerations, data bias, and emerging governance frameworks.
- Apply knowledge gained through an interactive quiz, reinforcing key terminology, concepts, and use cases presented during the session.
Module 1: What is AI & Introduction to Generative AI (GenAI)
- Lecture and Demo: Introduction to AI, history, and evolution. Overview of AI applications in different industries. Understanding generative AI, examples of GenAI (e.g., text generation, image creation).
Module 2: Survey of Public and Open Source Models/Tools
- Lecture and Demo: Overview of popular AI models and tools, both public and open-source (e.g., TensorFlow, PyTorch, Google Colab, Hugging Face).
Module 3: Multi-Modal Models & Prompt Engineering
- Lecture and Demo: Introduction to multi-modal models that handle text, images, and other data types. Techniques for crafting effective prompts to get desired outputs from AI models.
Module 4: Survey of Specialty/Niche Tools
- Lecture and Demo: Overview of specialty AI tools for image/media generation, data analysis, etc.
Module 5: Data Analysis & Visualization with AI
- Lecture and Demo: Using AI for data analysis and visualization with tools like Tableau and Power BI.
Is there a discount available for current students?
UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.
What is the cancellation and refund policy?
Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.