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Fundamentals of Modern AI

Group Training + View more dates & times


This comprehensive AI training program aims to introduce entry-level individuals to the fundamentals of Artificial Intelligence (AI) and its various applications. Through eight 3-hour modules, students will explore key AI concepts, tools, and ethical considerations. The course includes lectures, demonstrations, and hands-on labs, concluding with a final exam to assess understanding and readiness to apply AI knowledge in their careers.


24 class hours (Live Online or Classroom)

Who Should Take This Course


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.


Basic proficiency in internet navigation and Microsoft Office/Google Workspace. No prior AI knowledge is required.

Why You Should Take This Course
  1. Career Transition: Ideal for those seeking to start or advance a career in AI.
  2. Practical Skills: Hands-on experience with AI tools and technologies that are highly demanded in various industries.
  3. Comprehensive Coverage: Learn a wide range of AI applications, from general AI concepts to specialized tools and ethical considerations.
  4. Credential: Completion of the course and passing the final exam will provide a Certificate of AI Fundamentals competency.


“UMBC’s Fundamentals of Modern AI course is perfect for AI novice or enthusiasts for real, grounded and immediately applicable skills that can make them immediately relevant and valuable to current and potential employers.”

“The Fundamentals of Modern AI course provides a comprehensive and practical introduction to the world of artificial intelligence. Through engaging lectures, hands-on labs, and real-world examples, students gain a solid understanding of key AI concepts, tools, and applications that are highly relevant for today’s job market. Whether you’re looking to transition into an AI-related career or simply want to enhance your skills, this course is an excellent starting point that will equip you with the knowledge and confidence to start applying AI in your work.”

  • Jose Arrieta, CEO, imagineeer, former Chief Information Officer and Chief Data Officer of the United States Department of Health and Human Services.
Course Outline

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).
  • Lab: Basic AI exercises using simple tools like online AI demos and hands-on with simple GenAI tools like OpenAI’s DALL-E or ChatGPT.

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).
  • Lab: Setting up and experimenting with an open-source AI tool.

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.
  • Lab: Practical exercises using multi-modal models for tasks like image captioning and crafting/testing various prompts with AI models like GPT-3.

Module 4: Survey of Specialty/Niche Tools

  • Lecture and Demo: Overview of specialty AI tools for image/media generation, data analysis, etc.
  • Lab: Experimenting with tools like Adobe’s AI features, data analysis with AI-powered tools.

Module 5: Data Analysis & Visualization with AI

  • Lecture and Demo: Using AI for data analysis and visualization with tools like Tableau and Power BI.
  • Lab: Analyzing datasets and creating visualizations with AI

Module 6: Responsible AI, Accuracy Testing, and AI Security & Privacy

  • Lecture and Demo: Discussing ethical considerations, accuracy testing of AI models, and AI security/privacy concerns.
  • Lab: Exercises on evaluating AI model accuracy and implementing basic security measures.

Module 7: Disinformation & Critical Thinking and AI

  • Lecture and Demo: Understanding how AI can be used to spread disinformation and the importance of critical thinking in evaluating AI-generated content.
  • Lab: Exercises in identifying disinformation and applying critical thinking to AI-generated content.

Module 8: AI Co-pilots and Other Assistants

  • Lecture and Demo: Exploring AI-powered assistants like Microsoft Copilot, Google Assistant, and other productivity tools.
  • Lab: Hands-on activities with AI assistants to improve productivity and efficiency.

Final Exam

  • Format: A 1-hour test covering all the topics discussed in the
  • Objective: Assess students’ understanding and readiness to apply AI knowledge in practical

Additional Notes

  • Materials Provided: Lecture slides, demo scripts, lab instructions, and additional reading materials.
  • Support: Access to an online forum for discussions and Q&A with
  • Certification: Certificate of completion for students who pass the final exam.
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.

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