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ChatGPT Advanced: Mastering Multimodal AI Integration

Digital Innovation and Transformation 0 live data Cursustaal: EN

Cursustaal: EN Cursusbeschrijving, lesmateriaal en uitvoering blijven in het Engels.

Geen geplande sessies gevonden Contact us Tot 50% groepskorting beschikbaar.

Datum Dates on request

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Taal van de cursus en tweetalige begeleiding

Het officiële cursusmateriaal en het gedetailleerde programma zijn in het Engels. Uitleg, discussies, vragen en praktische oefeningen kunnen, afhankelijk van de beschikbaarheid van de trainer, tweetalig in het Engels en Nederlands worden verzorgd. Hierdoor behouden deelnemers toegang tot de originele Engelstalige vakterminologie, met aanvullende begeleiding in het Nederlands.

Seminarinhoud

Wat je leert

Why Attend

Artificial intelligence is rapidly evolving beyond text-based interactions into multimodal systems capable of processing and generating information across text, images, audio, video, and structured data. These developments are creating new opportunities for organisations to improve productivity, automate complex workflows, enhance customer experiences, and develop innovative digital services.

ChatGPT and related AI technologies enable professionals to interact with information through natural language while incorporating visual understanding, document analysis, voice interactions, data interpretation, and integrated business workflows. However, realising the full value of multimodal AI requires more than familiarity with conversational prompting.

Organisations must understand how different AI modalities work together, how to design effective multimodal prompts, how to integrate AI capabilities with enterprise systems, and how to evaluate the accuracy, reliability, security, and business value of AI-generated outputs.

Advanced applications also introduce challenges involving inconsistent model responses, hallucinations, sensitive information, system integration, computational costs, accessibility, and responsible AI governance. Successful implementation therefore requires a structured approach combining technical understanding, practical experimentation, workflow design, and organisational controls.

The ChatGPT Advanced: Mastering Multimodal AI Integration course provides participants with practical knowledge of advanced ChatGPT capabilities and multimodal AI integration techniques.

Participants explore multimodal prompting, image and document understanding, speech-based interactions, video analysis concepts, structured data processing, API integration, workflow automation, and the development of AI-enabled business applications.

Through practical demonstrations, guided exercises, and applied implementation workshops, participants develop the ability to design, evaluate, and deploy multimodal AI solutions that address real organisational challenges.

Professional Problems This Course Is Designed to Solve

Limited use of AI beyond text generation: Expanding ChatGPT applications to incorporate visual information, documents, audio, video, and structured business data.
Inconsistent results from complex AI prompts: Developing structured multimodal prompting techniques that improve instruction clarity, contextual understanding, and output reliability.
Disconnected AI tools and business systems: Designing integration workflows that connect AI capabilities with organisational applications, information sources, and operational processes.
Time-consuming document and information processing: Applying multimodal AI to analyse reports, extract information, interpret visual materials, and summarise complex content.
Difficulty developing practical AI applications: Understanding the architecture, implementation requirements, and evaluation methods for multimodal AI-powered solutions.
Concerns about AI accuracy and information security: Establishing validation, human oversight, privacy safeguards, and responsible AI controls for multimodal workflows.
Unclear return on AI investments: Identifying high-value use cases and measuring improvements in efficiency, quality, user experience, and operational performance.

Course Methodology

The programme combines instructor-led discussions, live demonstrations, hands-on ChatGPT exercises, multimodal prompting workshops, integration design activities, and practical AI application development scenarios.

Participants work with realistic business materials, including documents, spreadsheets, images, diagrams, audio transcripts, and illustrative video content, to explore how multimodal AI can support analysis, communication, decision-making, and workflow automation.

Technical demonstrations introduce API-based integration concepts, structured outputs, data processing workflows, and application architecture. Exercises can be adapted to participants' technical experience, with conceptual design activities for business professionals and optional implementation tasks for technical participants.

The programme emphasises practical experimentation, responsible AI use, output verification, and the development of reusable multimodal AI workflows.

Course Objectives

By the end of this course, participants will be able to:

Explain the principles and capabilities of multimodal generative AI systems
Identify appropriate business applications for text, image, audio, video, and structured data processing
Develop advanced prompts combining multiple information modalities
Apply ChatGPT to complex document and visual information analysis
Design effective speech-based and conversational AI interactions
Understand video interpretation workflows and their technical limitations
Integrate multimodal AI capabilities with business applications through APIs and automation tools
Develop structured AI workflows using external information and business data
Evaluate multimodal AI outputs for accuracy, consistency, relevance, and reliability
Apply privacy, security, accessibility, and responsible AI principles
Assess the operational and financial value of multimodal AI applications
Design a practical multimodal AI integration solution for an organisational use case

Target Audience

This course is suitable for:

Digital transformation managers and specialists
Artificial intelligence and innovation professionals
IT managers and enterprise technology specialists
Business analysts and process improvement professionals
Software developers and application integration specialists
Data analysts and business intelligence professionals
Product managers and digital service designers
Marketing, communication, and content development professionals
Customer experience and service automation managers
Business leaders responsible for AI adoption and digital innovation

Target Competencies

Participants will develop competencies in:

Multimodal AI capabilities and application design
Advanced ChatGPT prompting techniques
Visual and document intelligence
Audio and conversational AI workflows
Video and multimodal information analysis
AI API integration and workflow automation
Structured data processing and AI orchestration
Multimodal output evaluation and validation
Responsible AI, privacy, and security governance
AI solution development and business value assessment

Seminardetails

Gedetailleerde opbouw

Day 1: Advanced ChatGPT Capabilities and Multimodal AI Foundations

Understanding the evolution of generative AI from text-based language models to multimodal systems that process text, images, audio, video, and structured information
Exploring the capabilities, limitations, and practical differences between multimodal input processing, reasoning, and content generation
Examining advanced ChatGPT features, model selection considerations, context management, and available multimodal interaction methods
Developing advanced prompting strategies using role definition, task decomposition, contextual information, examples, output constraints, and iterative refinement
Understanding how to combine textual instructions with images, documents, tables, and other inputs to improve task execution and contextual interpretation
Practical workshop: Designing and testing advanced multimodal prompts for business analysis, visual interpretation, document review, and structured information extraction

Day 2: Image Intelligence, Document Understanding and Visual AI Applications

Applying multimodal AI to interpret images, diagrams, charts, screenshots, and visual business information
Analysing complex documents containing text, tables, figures, financial information, and mixed visual layouts
Designing document intelligence workflows for classification, summarisation, information extraction, comparison, and question answering
Exploring image generation and editing workflows, including prompt design, creative iteration, visual consistency, and quality evaluation
Understanding visual AI limitations involving image resolution, ambiguous content, numerical accuracy, document structure, and unsupported visual assumptions
Hands-on exercise: Developing a multimodal document analysis workflow that extracts information, evaluates visual content, generates structured findings, and applies human verification

Day 3: Audio, Voice, Video and Real-Time Multimodal Interactions

Understanding speech recognition, speech synthesis, audio understanding, and conversational AI capabilities within multimodal systems
Designing voice-enabled workflows for customer interactions, meeting assistance, language support, accessibility, and internal knowledge retrieval
Exploring audio transcription, speaker-related considerations, summarisation, and extraction of action items from spoken information
Understanding video analysis concepts, including frame interpretation, temporal context, scene understanding, and the challenges of processing extended video sequences
Examining real-time multimodal interaction architectures, latency considerations, session management, user experience, and error handling
Practical workshop: Designing a voice-enabled assistant and a video or audio analysis workflow with clear inputs, outputs, validation procedures, and operational safeguards

Day 4: Multimodal AI Integration, APIs and Intelligent Workflow Automation

Understanding multimodal AI integration architecture, including application interfaces, API requests, model inputs, structured responses, and external system connections
Exploring the use of OpenAI APIs and relevant development tools to process supported combinations of text, images, audio, and other media
Designing workflows that connect AI services with document repositories, business applications, databases, and automation platforms
Applying structured outputs, function calling concepts, retrieval-augmented generation, and workflow orchestration to support reliable AI-enabled processes
Evaluating integration challenges involving authentication, access permissions, data transfer, error handling, latency, scalability, and operational costs
Integration workshop: Designing an end-to-end multimodal AI workflow that receives business information, processes multiple input types, produces structured outputs, and routes results for human review

Day 5: Responsible Multimodal AI, Performance Evaluation and Enterprise Deployment

Establishing evaluation methods for multimodal AI applications covering accuracy, relevance, completeness, consistency, latency, usability, and business effectiveness
Identifying multimodal AI risks involving hallucinations, prompt injection, misleading visual interpretation, sensitive information exposure, intellectual property, and inappropriate automation
Applying responsible AI principles through human oversight, access controls, data minimisation, output validation, transparency, and documented governance procedures
Developing deployment strategies covering pilot selection, technical readiness, stakeholder engagement, user training, operational monitoring, and continuous improvement
Assessing multimodal AI business cases through implementation costs, productivity improvements, quality indicators, risk reduction, and return on investment
Capstone exercise: Developing and presenting a Comprehensive Multimodal AI Integration Solution incorporating a defined business use case, advanced prompting strategy, multimodal processing workflow, integration architecture, evaluation criteria, security controls, and implementation roadmap

Data en locaties

Beschikbare seminar data

50% KORTING VOOR GROEPEN

0 data

Geen geplande sessies gevonden Er staan momenteel geen komende data voor deze cursus vermeld. Neem contact met ons op voor informatie over toekomstige data.

Cursuscertificaat

Certificaat bij afronding

Iedere deelnemer die dit seminar afrondt, ontvangt een professioneel cursuscertificaat van INFORMATECH.

Deelnemers ontvangen een INFORMATECH-certificaat voor het afronden van ChatGPT Advanced: Mastering Multimodal AI Integration.
Het certificaat bevestigt aanwezigheid en succesvolle deelname aan het seminar.
Het ondersteunt registraties voor professionele ontwikkeling binnen digital innovation and transformation en aanverwante functies.

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Wanneer is mijn plaats bevestigd?

Je plaats is bevestigd zodra de volledige betaling is ontvangen.

Bieden jullie groepskortingen aan?

Ja, wij bieden de volgende kortingen voor groepsboekingen:

2 deelnemers: 20% korting
3 deelnemers: 30% korting
4 deelnemers: 35% korting
5 of meer deelnemers: 50% korting

Kunnen kortingen worden gecombineerd met andere aanbiedingen?

Nee, kortingen kunnen niet worden gecombineerd tenzij dit uitdrukkelijk is vermeld.

Welke betaalmethoden accepteren jullie?

Wij accepteren bankoverschrijvingen, credit-/debitcards en geselecteerde online betaalmethoden.

Wanneer moet ik betalen?

De volledige betaling moet vóór de startdatum van de cursus zijn voldaan om je deelname te bevestigen.

Is btw inbegrepen in de cursusprijs?

De btw-behandeling hangt af van je locatie en status:

EU-bedrijven (met geldig btw-nummer): btw kan worden verlegd (0%)
EU-particulieren (zonder btw-nummer): btw is van toepassing volgens lokale regels
Deelnemers buiten de EU: btw is doorgaans niet van toepassing (0%)

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Kan ik mijn inschrijving annuleren?

Ja, annuleringen moeten schriftelijk worden ingediend.

Wat is jullie terugbetalingsbeleid?

Meer dan vijfenveertig (45) kalenderdagen vóór de startdatum van de cursus: de deelnemer heeft recht op volledige terugbetaling van de betaalde trainingskosten.
Tussen eenendertig (31) en vijfenveertig (45) kalenderdagen vóór de startdatum van de cursus: de deelnemer heeft recht op terugbetaling van vijftig procent (50%) van de betaalde trainingskosten.
Dertig (30) kalenderdagen of minder vóór de startdatum van de cursus: de trainingskosten worden niet terugbetaald.

Kan ik mijn plaats aan iemand anders overdragen?

Ja, vervanging is zonder extra kosten mogelijk als dit vóór de startdatum van de cursus wordt aangevraagd.

Wat gebeurt er als de cursus wordt uitgesteld of geannuleerd?

Wij behouden ons het recht voor om een cursus te verplaatsen of te annuleren door onvoorziene omstandigheden. In dat geval kun je:

overstappen naar een andere datum
een volledige terugbetaling ontvangen

Ontvang ik een certificaat?

Ja, alle deelnemers ontvangen na deelname een certificaat van afronding.

Is aanwezigheid verplicht?

Ja, volledige aanwezigheid is vereist om certificering te ontvangen.

Zijn jullie cursussen online of fysiek?

Wij bieden zowel klassikale als virtuele live online trainingen aan.

Worden cursusmaterialen verstrekt?

Ja, alle deelnemers ontvangen trainingsmaterialen in digitale vorm.

Zijn reis en accommodatie inbegrepen?

Nee, deelnemers zijn zelf verantwoordelijk voor reis en accommodatie tenzij anders vermeld.

Kunnen jullie maatwerk of incompany training verzorgen?

Ja, wij bieden trainingsprogramma’s op maat op basis van de behoeften van jouw organisatie.

Hoe kan ik contact opnemen voor ondersteuning?

Je kunt ons bereiken via e-mail op info@informatech.co.uk of via ons contactformulier. Ons team reageert snel.

In welke taal wordt de cursus gegeven?

Het officiële cursusmateriaal is in het Engels. Afhankelijk van de beschikbaarheid van de trainer kunnen uitleg, discussies en praktische oefeningen in het Engels en Nederlands worden verzorgd.

Is het cursusmateriaal in het Nederlands beschikbaar?

Het officiële cursusmateriaal en het gedetailleerde programma blijven in het Engels, zodat deelnemers met de internationaal gebruikte vakterminologie kunnen werken.

ChatGPT Advanced: Mastering Multimodal AI Integration

Locatie Venue on request

Datum Dates on request

Belangrijkste onderwerpen

Day 1: Advanced ChatGPT Capabilities and Multimodal AI Foundations Understanding the evolution of generative AI from text-based language models to multimodal systems that process text, images, audio, video, and structured information Exploring the capabilities, limitations, and practical differences between multimodal input processing, reasoning, and content generation Examining advanced ChatGPT features, model selection considerations, context management, and available multimodal interaction methods Developing advanced prompting strategies using role definition, task decomposition, contextual information, examples, output constraints, and iterative refinement Understanding how to combine textual instructions with images, documents, tables, and other inputs to improve task execution and contextual interpretation Practical workshop: Designing and testing advanced multimodal prompts for business analysis, visual interpretation, document review, and structured information extraction Day 2: Image Intelligence, Document Understanding and Visual AI Applications Applying multimodal AI to interpret images, diagrams, charts, screenshots, and visual business information Analysing complex documents containing text, tables, figures, financial information, and mixed visual layouts Designing document intelligence workflows for classification, summarisation, information extraction, comparison, and question answering Exploring image generation and editing workflows, including prompt design, creative iteration, visual consistency, and quality evaluation Understanding visual AI limitations involving image resolution, ambiguous content, numerical accuracy, document structure, and unsupported visual assumptions Hands-on exercise: Developing a multimodal document analysis workflow that extracts information, evaluates visual content, generates structured findings, and applies human verification Day 3: Audio, Voice, Video and Real-Time Multimodal Interactions Understanding speech recognition, speech synthesis, audio understanding, and conversational AI capabilities within multimodal systems Designing voice-enabled workflows for customer interactions, meeting assistance, language support, accessibility, and internal knowledge retrieval Exploring audio transcription, speaker-related considerations, summarisation, and extraction of action items from spoken information Understanding video analysis concepts, including frame interpretation, temporal context, scene understanding, and the challenges of processing extended video sequences Examining real-time multimodal interaction architectures, latency considerations, session management, user experience, and error handling Practical workshop: Designing a voice-enabled assistant and a video or audio analysis workflow with clear inputs, outputs, validation procedures, and operational safeguards Day 4: Multimodal AI Integration, APIs and Intelligent Workflow Automation Understanding multimodal AI integration architecture, including application interfaces, API requests, model inputs, structured responses, and external system connections Exploring the use of OpenAI APIs and relevant development tools to process supported combinations of text, images, audio, and other media Designing workflows that connect AI services with document repositories, business applications, databases, and automation platforms Applying structured outputs, function calling concepts, retrieval-augmented generation, and workflow orchestration to support reliable AI-enabled processes Evaluating integration challenges involving authentication, access permissions, data transfer, error handling, latency, scalability, and operational costs Integration workshop: Designing an end-to-end multimodal AI workflow that receives business information, processes multiple input types, produces structured outputs, and routes results for human review Day 5: Responsible Multimodal AI, Performance Evaluation and Enterprise Deployment Establishing evaluation methods for multimodal AI applications covering accuracy, relevance, completeness, consistency, latency, usability, and business effectiveness Identifying multimodal AI risks involving hallucinations, prompt injection, misleading visual interpretation, sensitive information exposure, intellectual property, and inappropriate automation Applying responsible AI principles through human oversight, access controls, data minimisation, output validation, transparency, and documented governance procedures Developing deployment strategies covering pilot selection, technical readiness, stakeholder engagement, user training, operational monitoring, and continuous improvement Assessing multimodal AI business cases through implementation costs, productivity improvements, quality indicators, risk reduction, and return on investment Capstone exercise: Developing and presenting a Comprehensive Multimodal AI Integration Solution incorporating a defined business use case, advanced prompting strategy, multimodal processing workflow, integration architecture, evaluation criteria, security controls, and implementation roadmap

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