AI Essentials
Overview
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.
This course is included in the AI Learning Subscription.
Schedule
Register 21 days before class start date and save 10%! Enter discount code EARLY10 during registration.
Duration: 4 Hours
Dates
Times
Location
Price
Prerequisites
Who Should Take This Course
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.
Why You Should Take This Course
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.
Course Outline
AI Essentials
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.