Course Outline
Module 1: Overview of No-Code Artificial Intelligence Capabilities
- Generative AI capabilities in 2026: an overview of available features without programming
- Mechanisms of large language models and multimodal systems, explained in accessible terms
- Survey of leading platforms: Claude, ChatGPT, Gemini, and specialized tools for image generation and workflow automation
- Construction of effective prompts and parameters: defining tasks, inputs, desired outputs, constraints, and stylistic elements
Practical exercises and application task: Orient participants within the environment and execute initial structured prompts using a modern AI assistant. Subsequently, draft prompt structures for a specific task within the participant’s existing operational workflow.
Module 2: Operational Use of AI Assistants
- Initial setup and navigation of ChatGPT, Claude, and Gemini
- Core functional capabilities: drafting, content transformation, summarization, and analytical processing
- Processing multimodal inputs, including file uploads and image analysis
- Applications for data generation, format conversion, and routine operational tasks
- Conducting data analysis within assistant interfaces without programming requirements
- Utilizing extensions, plugins, and integrated third-party tools
Practical exercises and application task: Initiate interaction with each assistant platform, explore core capabilities, and execute data generation and analytical tasks. Application task: Integrate a selected AI assistant into a specific component of the participant’s operational workflow.
Module 3: AI Applications for Document and Data Management
- Techniques for summarizing, extracting key information, and comparing document sets
- Performing data analysis and generating basic visualizations from spreadsheet and dataset inputs
- Implementing AI-assisted search and browsing functions, including the use of browser extensions
- Developing custom, reusable assistants: Configuration of custom GPTs, Claude Projects, and Gemini Gems
- Anchoring assistant responses to specific organizational documents without code implementation
Practical exercises and application task: Analyze a defined set of documents, execute an AI-facilitated data analysis, and configure a custom assistant. Application task: Incorporate an AI-driven document or data workflow into daily operational procedures.
Module 4: Generative AI for Image Production
- Current 2026 image generation landscape: Adobe Firefly, GPT-Image, Midjourney, and Google Imagen
- Text-to-image generation: Creation of original artistic content and professional visual assets
- Control of generation parameters: Adjusting style, composition, aspect ratio, and iterative refinement
- Modifying existing imagery using generative fill, expansion, and object-specific editing tools
- Application of branding standards, customization, and targeted image processing for organizational needs
Practical exercises and application task: Generate original imagery, refine outputs using specific parameters, apply generative fill edits, and utilize combined toolsets. Application task: Produce a cohesive set of branded images for a defined operational scenario.
Module 5: No-Code Automation and Autonomous AI Agents
- Overview of no-code automation platforms: Zapier, Make, Microsoft Power Automate, and Copilot Studio
- Designing workflows: Connecting triggers to actions to establish automated processes
- Integrating AI functions into workflows: Summarization, classification, drafting, extraction, and routing
- Transition from basic automation to autonomous agents: AI systems that utilize tools and execute multi-step actions
- Understanding open standards, including the Model Context Protocol
- Maintaining human oversight: Implementing approval gates and establishing safe operational boundaries
Practical exercises and application task: Construct a no-code automation workflow that utilizes AI to process incoming items from initiation to completion. Application task: Design and implement an automation solution for a specific, real-world operational workflow.
Module 6: Enterprise Integration, Governance, and Capstone Project
- Generative AI as a service and enterprise-grade artificial intelligence tools
- Data privacy, security protocols, and responsible usage frameworks in organizational settings
- Developing knowledge-grounded assistants for enterprise use without code
- Integrating AI tools into established operational processes
- Capstone Project: Synthesizing assistants, data processing, image generation, and automation into a unified workflow
Practical exercises and capstone project: Develop and present a no-code AI solution that integrates course tools into a functional workflow. Application task: Conclude with a working solution and a comprehensive 30-day implementation plan.
Requirements
- Proficiency in using web browsers and standard office software.
- No prior experience with generative artificial intelligence is necessary.
- No background in programming is required.
Intended Audience
- Analysts, marketing personnel, and sales or pre-sales staff requiring operational AI solutions.
- Business and data analysts responsible for producing documents, reports, and visual assets.
- Project and product personnel integrating AI into existing operational processes.
- Application developers seeking a no-code introduction to AI tooling for government or enterprise applications.
Testimonials (4)
Understanding of AI and LLM. How it works and ehat the watchouts and opportunities are!
Henk Jan Beltman - genuine business
Course - Advanced AI Concepts with Perplexity
Comprehensiveness about the backround; how to do a prompt.
Olaf Kannt - Helios Klinikum Krefeld
Course - Generative AI and Prompt Engineering in Healthcare
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
use of proper and effective prompt
