CertNexus - GenAIBIZ

Varighed:

Kun 2 dage

Metode:

Klasseværelse / Online / Hybrid

Næste dato:

10/2/2025 (Mandag)

Overview

On this accelerated CertNexus GenAIBIZ course you will gain an understanding of what generative AI is, how it relates to and can benefit business functions, how to identify potential risks, and how to identify the challenges and milestones of implementing generative AI and becoming a generative AI–driven organization.

At the end of this course, you’ll sit the CertNexus exam, and achieve your CertNexus GenAIBIZ certification. Through Firebrand’s Lecture | Lab | Review methodology, you’ll get certified at twice the speed of the traditional training and get access to courseware, learn from certified instructors, and train in a distraction-free environment.

Audience

This course is ideal for:

Business leaders, consultants, product and project managers, and other decision makers who are interested in growing the business by leveraging the power of generative AI. Other business professionals who wish to explore generative AI solutions are also candidates for this assessment.

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Benefits

Er du klar til kurset? Tag en GRATIS test som hjælper dig med at bedømme din nuværende viden.

Gratis Test

Curriculum

Module 1: Identify AI Fundamentals [20%]

Define fundamental AI terms and concepts.

Artificial Intelligence
- General vs. narrow AI
- Recent history/timeline
- Enabling technologies
Machine Learning
- Algorithm vs. model
- Datasets
- Approaches (supervised vs. unsupervised)
Deep Learning
- ANN
- Network parameters/weights
- Hyperparameters
- Applications
  - NLP
  - Computer vision
Model checkpoints

Define generative AI terms and concepts.

Generative AI
- Key organizations
- Key resources
Generative AI modalities
- Text
- Code
- Images
- Video
- Audio
- Multimodal
Generative AI approaches
- GAN
- VAE
- GPT
- Diffusion
- RLFH
Prompting
- Prompt engineering
- In-context prompting
Fine-tuning models
API access

Module 2: Solve Business Problems with AI-Generated Content [35%]

Generate text using AI.
LLM
Tokens
Approaches
- Text generation
- Text completion
- Chatbots
- Speech to text
- Transcription
- Assistive AI with text outputs
Prompt engineering for text generation
Fine-tuning text models
Common text generation tools
- OpenAI GPT models
- ChatGPT
- Bard
- LLaMA
- Microsoft 365 Copilot
- Duet AI
- Whisper
Business use cases
- Customer service
- Online ordering systems
- Marketing campaigns
- Information summarization
- Information mining and inference
- Language translation
- Interviews and onboarding
Generate code using AI.
- Approaches
  - Code generation
  - Code completion
  - Code refactoring
  - Code testing
  - Code debugging
  - Code commenting and documentation
  - Assistive AI with code outputs
- Prompt engineering for code generation
- Fine-tuning code models
- Common code generation tools
  - OpenAI Codex
  - GitHub Copilot
  - Amazon CodeWhisperer
  - Duet AI
  - CodeT5
  - CodeGen
- Business use cases
  - Rapid/agile development
  - Project management
  - DevOps
  - Proof of concept
  - Software prototyping
  - QA
  - Performance optimization
  - Software security
Generate images and video using AI.
- Image approaches
  - Text to image
  - Image to image
  - Image editing and inpainting
  - Image control
  - Image upscaling
  - Assistive AI with image outputs
- Video approaches
  - Text to video
  - Image to video
  - Text + image to video
  - Video to video
  - Frame interpolation
  - Video customization
  - Assistive AI with video outputs
- Prompt engineering for image and video generation
- Fine-tuning image and video models
- Common image generation tools
  - DALL·E
  - Craiyon
  - Midjourney
  - Stable Diffusion
  - DreamBooth
  - Imagen
- Common video generation tools
  - Synthesia
  - Rephrase Studio
  - Make-A-Video
  - Runway
- Business use cases
  - Promotional materials
  - Press releases
  - Training materials
  - Games/virtual worlds
- Corporate branding
- Data visualization
- Product design and prototyping
- Website and app styling
- Product listings
- Medical imaging and diagnostics
Generate audio using AI.
- Approaches
  - Text to audio
  - Audio to audio
  - Audio editing and cleaning
  - Assistive AI with audio outputs
- Prompt engineering for audio generation
- Fine-tuning audio models
- Common audio generation tools
  - Jukebox
  - VALL-E
  - MusicLM
  - ElevenLabs
- Business use cases
  - Audio assets
    - Promotional materials
    - Press releases
    - Training materials
    - Games/virtual worlds
- Voiced chatbots/assistants
- Accessibility
- Localization
- Language learning

Module 3: Identify Generative AI Challenges [25%]

Identify shortcomings of generative AI.
- Confabulation/hallucination
- Misinformation and misleading content
- Cost
  - Monetary cost of implementation
  - Training time cost
  - Output time cost
- Lack of fine-tuned control
- Limitations of training data
- Hardware requirements
- Reliance on external factors
  - Cloud services
  - Foundational models
- Industry-specific risks
- Adversarial vulnerabilities
Identify ethical risks of generative AI.
- Privacy issues
- Accountability issues
- Transparency/explainability issues
- Bias/discrimination issues
- Safety/security issues
Identify business concerns of generative AI.
- Governance
- Employee impact
- Future of work
- Operational risks
- Data risks
- Brand reputation/consumer trust risks
- Legal issues
  - Intellectual property/copyright
  - AI laws and regulations

Module 4: Implement Business Strategies for Generative AI [20%]

Apply best practices for implementing generative AI in the organization.
- Project factors
  - Scope
  - Strategy
  - Objectives
  - Goals
  - Requirements
- Alignment with initiatives
  - Organizational initiatives
  - ESG initiatives
  - Ethics and compliance initiatives
- Acquisition
  - Resources
  - Job expertise
- Education
  - End users
  - Employees
- Selection of generative AI
  - Modalities
  - Tools
- IT strategy and infrastructure
  - Data and tools used in fine tuning
  - Tech stack for implementing generative AI
  - Cloud vs. on-premises resource allocation
- Change management
  - Change agents
  - Knowledge translators
  - Humans in the loop
- Prototyping
Evaluate the results of generative AI projects.
- Business analyses
  - Business impact analysis
  - Comparative analysis
- User feedback
  - Collection
  - Analysis
- Usage of generative AI systems
  - Monitoring
  - Analysis
- KPIs
- Adverse results from generative AI systems
  - Project limitations
  - Undesirable outcomes
- Long-term sustainability

Exam Track

At the end of this accelerated course, you’ll sit the following exam at the Firebrand Training centre, covered Certification Guarantee:

CertNexus GenAIBIZ Exam (GAZ-110)

Upon successful completion of the GAZ-110 assessment, business professionals will demonstrate an understanding of what generative AI is, how it relates to and can benefit business functions, how to identify potential risks, and how to identify the challenges and milestones of implementing generative AI and becoming a generative AI–driven organization.

Duration: 20–45 minutes
Format: Multiple Choice/Multiple Response
Number of questions: 25
Passing score: 76% or 19/25 items
Domains:
- Identify AI Fundamentals 20%
- Solve Business Problems with AI-Generated Content 35%
- Identify Generative AI Challenges 25%
- Implement Business Strategies for Generative AI 20%

What's Included

Det hele er inkluderet! Du får en alt-inklusiv kursuspakke, som er målrettet til dine behov. Vi tager os af enhver detalje, så det eneste du skal fokusere på er dine lærings- og certificeringsmål.

Transport til/fra specifikke afhentningssteder
Overnatninger, samtlige måltider samt adgang til forfriskninger, snacks, kaffe og the.
Intensiv Hands-on uddannelse med vores unikke (Lecture | Lab | Review)TM metode
Omfattende kursusmaterialer og labmanualer
Et helt igennem instruktørstyret program
24 timers adgang til både undervisningslokale og instruktøren
Samtlige måltider samt adgang til forfriskninger, snacks, kaffe og the.
Certificeringsgaranti

Prerequisites

Before attending this accelerated course, you should have:

Fundamental knowledge of business processes and general business concepts, as well as domain knowledge in generative AI. It is recommended that candidates acquire domain knowledge by attending the CertNexus® GenAIBIZ (Exam GAZ-110): Making ChatGPT and Generative AI Work for You course prior to taking the assessment.

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Kursusdatoer

Starter	Slutter	Tilgængelighed	Sted
26/8/2024 (Mandag)	27/8/2024 (Tirsdag)	Afsluttet - Giv feedback	-

10/2/2025 (Mandag)	11/2/2025 (Tirsdag)	Begrænsede pladser	Landsdækkende
24/3/2025 (Mandag)	25/3/2025 (Tirsdag)	Tilgængelige pladser	Landsdækkende
5/5/2025 (Mandag)	6/5/2025 (Tirsdag)	Tilgængelige pladser	Landsdækkende
16/6/2025 (Mandag)	17/6/2025 (Tirsdag)	Tilgængelige pladser	Landsdækkende