Cisco AI Business Practitioner (AIBIZ)

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About Course

Cisco AI Business Practitioner (AIBIZ) is a foundational certification designed to help professionals understand how Artificial Intelligence creates value in modern businesses. It covers core AI concepts, data fundamentals, machine learning basics, and the practical use of AI in organizational decision-making. The certification focuses on real-world business applications such as automation, predictive analytics, customer experience enhancement, and operational efficiency. AIBIZ also emphasizes responsible AI, governance, and risk-aware adoption strategies. It is ideal for non-technical professionals, managers, consultants, and leaders who want to leverage AI to drive innovation, improve productivity, and support strategic digital transformation initiatives within their organizations.

Course Content

One On One Training

Module 1- Foundational Generative AI Concepts

Module 2- Tool Practice & Platform Evaluation

Module 3- Prompt Engineering

Module 4- Content Generation

Module 5- Responsible AI & Risk Management

Module 6- Evaluation of AI Outputs

Module 7- AI for Data Analysis & Research

Module 8- Technical Concepts & Integration

Module 9- Strategic Leadership & Business Adoption

Cisco AI Business Practitioner (AIBIZ)

About Course

What Will You Learn?

Course Content

One On One Training

Module 1- Foundational Generative AI Concepts

Understand key AI models: Large Language Models (LLMs), diffusion models, audio/code generation

Learn AI capabilities and limitations.

Module 2- Tool Practice & Platform Evaluation

Explore major AI platforms: chatbots, image generators, research tools.

Evaluate them on performance, security, compliance, and cost.

Module 3- Prompt Engineering

Create clear, persona-based prompts.

Use iterative refinement and advanced techniques for business-specific tasks.

Module 4- Content Generation

Generate professional text: emails, reports.

Create visual content: marketing graphics, images

Produce audio content: voiceovers, narration, etc.

Module 5- Responsible AI & Risk Management

Identify and mitigate algorithmic bias.

Understand data privacy, regulatory concerns, and security in AI.

Develop responsible AI policies within teams.

Module 6- Evaluation of AI Outputs

Detect hallucinations, factual inaccuracy, and bias in model outputs.

Learn strategies to correct, regenerate, or refine AI-generated content.

Module 7- AI for Data Analysis & Research

Use AI for exploratory data analysis (EDA).

Generate visualizations, identify patterns, formulate hypotheses

Structure research, summarise information, produce insights

Module 8- Technical Concepts & Integration

Grasp core API concepts (authentication, key management).

Learn cost-management strategies when integrating AI (using APIs).

Understand security principles around AI integration

Module 9- Strategic Leadership & Business Adoption

Build your personal AI “toolbox” / roadmap for integration

Identify high-value AI use cases in business

Manage organizational change: pilot projects, best practices, team adoption.

Make a business case for AI adoption (ROI, governance, scaling).