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This course gives you a comprehensive introduction to Generative AI, covering everything from its fundamentals to its practical applications. You’ll learn about the differences between Generative AI and other types of AI, and explore models such as transformers and GANs to generate text, images, audio, and more. In addition, you will master prompt engineering to optimize results in various tasks.
The course also addresses the ethical and societal implications of AI, such as data privacy, intellectual property, and biases. Ideal for those who want to understand and apply AI in professional and creative contexts.
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Duration
70h (Online)
Objectives
This course teaches you the skills needed to successfully complete the Generative AI Fundamentals certification offered by Certiport. These skills are introduced through various types of exercises and review materials.
Upon completion of this course, you will understand:
- Understand the key concepts of Generative AI: Explore the essential methods of AI, including transformers, GANs, and broadcast models, and how they produce outputs such as text, images, video, and audio.
- Master basic prompt engineering: Learn how to create and modify effective prompts to generate and transform content, adapting the results to specific tasks and media formats.
- Refine prompt techniques: Improve prompt clarity and accuracy by using common strategies, such as zero-shot and few-shot prompting, for more accurate and focused AI responses.
- Recognize ethical and social impacts: It comprises key ethical considerations, such as bias, data privacy, and legal implications, and explores the broader societal impacts of using AI in various fields.
Program
UNIT 1: Introduction
- Module objectives and key terms.
- Artificial Intelligence.
- Generative AI.
- Predictive AI.
- Discriminative AI.
- Analytical AI.
- Statistical AI.
- AI vs. AI Search Engines.
- Module objectives and key terms.
- Text models.
- Image models.
- Large language models.
- Dissemination.
- Transformer.
- Variational autoencoders.
- Generative Antagonistic Networks.
- Convolutional Neural Networks.
- Model training.
- Module objectives and key terms.
- Understand the input and output.
- Types of input.
- Types of output.
- Customization.
- AI tools.
- Selecting a tool.
- Objectives of the Module and key terms.
- Conversational models.
- ChatGPT.
- Microsoft Copilot.
- Google Gemini.
- Meta AI.
- Adobe Express.
- Claude.
- Microsoft Azure AI Studio.
- Stable Diffusion.
- DALL-E.
- Adobe Firefly.
- Objectives of the Module and key terms.
- Reliability.
- Technology requirements.
- Privacy.
- Lack of standards.
- Consistency.
- Obsolescence.
UNIT 2: Prompts engineering
- Module objectives and key terms.
- Collect content.
- Summarize.
- Create and ideate.
- Module objectives and key terms.
- Reformat content.
- Edit and proofread.
- Visualize.
- Transform media type.
- Personalize and adapt.
- Produce an image.
- Explore artistic ideas.
- Transform an image.
- Describe an image.
- Add movement.
- Interpolate.
- Coloring.
- Generate video.
- Generate an avatar.
- Add and remove objects.
- Subtitles.
UNIT 3: Refinement of Prompts
- Module objectives and key terms.
- Specificity.
- Clarity.
- Avoid assumptions.
- Style and tone.
- Style guide.
- Person.
- Context.
- Module objectives and key terms.
- Examples.
- Glossary.
- Templates.
- Research papers.
- Previous conversations.
- Module objectives and key terms.
- Zero-Shot.
- Few-Shot.
- Chain-of-Thought.
- Self-consistency.
- Generate knowledge.
- Prompt chaining.
- Reverse prompting.
- Module objectives and key terms.
- Verify historical facts.
- Verify current facts.
- Verify numerical data.
UNIT 4: Ethics
- Module objectives and key terms.
- Bias in AI.
- Training data.
- Guardrails.
- Prompts.
- Common biases.
- Module objectives and key terms.
- Intellectual property.
- Inappropriate use.
- Transparency.
- Module objectives and key terms.
- Importance of privacy.
- Training.
- Identity theft.
- Company policies.
- Human-generated content.
- Module objectives and key terms.
- Supervision.
- Responsibility.
- Legal action.
- Dangerous purposes.
- Negative impacts.
- Positive impacts.
