About the Course

Generative Artificial Intelligence (GenAI) has rapidly transformed how organizations innovate, create content, and automate tasks by enabling machines to produce entirely new, original outputs rather than simply classifying or analyzing existing data. From marketing teams using AI- generated images and copy to accelerate campaign launches, to software engineers leveraging code-generation tools that boost developer productivity, the impact of GenAI spans virtually every industry. In 2024 alone, global investment in GenAI startups surpassed $20 billion, and leading enterprises report up to 40 percent reductions in content-creation time and 30 percent improvements in prototype development cycles.

Starting with the inner workings of modern generative architectures, we will delve into best practices for prompt design, practical workflows for fine-tuning and evaluation, multimodal integration techniques, and ethical frameworks that safeguard responsible AI adoption. By course end, you’ll have both the conceptual grounding and the practical skill set to lead GenAI initiatives that drive real business value.

Target Participants

This course is ideal for professionals, content creators, data analysts, product managers, and anyone curious about applying generative AI in their workflows.

What You Will Learn

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

• Explain core concepts and architectures underlying generative AI
• Craft effective prompts to guide text, image, audio, and code generation
• Customize pre-trained models via fine-tuning for specific tasks
• Assess and mitigate ethical and bias-related risks in generative outputs
• Prototype and deploy a simple generative AI application

Training Dates

One week

Course Outline

Introduction to Generative AI & Foundations

• Evolution of AI: From rule-based to generative
• Key architectures
• Overview of popular GenAI models
• Generative AI use-cases across industries
• Setting up your development environment

Prompt Engineering & Text Generation

• Anatomy of a prompt: instructions, context, constraints
• Zero-, one-, and few-shot prompting
• Controlling tone, style, and length
• Chain-of-thought prompting techniques
• Mitigating hallucinations and bias

Multimodal Generative AI: Images, Audio & Code

• Text-to-image models
• Text-to-speech and speech-to-text workflows
• Code generation with Codex and Copilot
• Integrating multimodal outputs
• Practical demo: Building a simple chatbot with image support

Fine-Tuning & Customization

• When and why to fine-tune vs. prompt-tune
• Data collection and curation best practices
• Transfer learning workflows
• Evaluating model performance (perplexity, human eval)
• Deployment considerations (APIs vs. self-hosting)

Ethics, Governance & Future Trends

• Ethical challenges: bias, misinformation, deepfakes
• Data privacy and IP considerations
• Responsible AI frameworks and policies
• Emerging research directions

Training Approach

This course is delivered by our seasoned trainers who have vast experience as expert professionals in their respective fields of practice. The course is taught through a mix of practical activities, presentations, group works and case studies.

Training notes and additional reference materials are provided to the participants.

Certification

Upon successful completion of this course, participants will be issued a certificate.

Tailor-Made Course

We can also do this as a tailor-made course to meet organization-wide needs.