Certificate Course in Prompt Engineering & Generative AI

Trace the shift from traditional programming to neural networks and generative AI, showing how it understands concepts and creates new text, images, music, or code.

Discover how AI agents act on behalf of users to achieve goals. From checking calendars to ordering cat food, they interact with tools and environments to perform tasks automatically.

Explore how large language models power generative ai by understanding and generating human language, enabling natural language processing (NLP), translation, summarization, and question answering.

Explain AI hallucination in which LLMs like ChatGPT generate false information as facts, why it happens (prediction over fact-checking, data gaps, ambiguous prompts), and how to mitigate with sources.

Discover retrieval augmented generation (rag) that uses a retriever with external data to reduce hallucinations, and explore embeddings, vector databases, and frameworks like lang chain and lama index.

Learn to craft clear, effective prompts for large language models to elicit high-quality results, and see how prompt engineering tailors outputs for onboarding programs.

Learn how prompts are built from task, context, input data, and output format to elicit precise and actionable responses from artificial intelligence.

Explore zero-shot, one-shot, and few-shot prompting in prompt engineering, and learn how the number of examples shapes AI understanding and control.

Learn how prompt modifiers shape AI output by guiding style, tone, and format. The lecture covers length modifiers, bullet points, perspective and role-based modifiers, and scenario-based examples.

Explore how AI models differ from fixed machines, distinguish modifiers from parameters, and learn how tokens, temperature, top k, and top p shape prompts and responses.

Explore advanced prompting techniques such as chain of thought prompting, iterative prompting, and tree of thoughts to improve accuracy and decision-making.

AI agents integrate a brain-like LLM with short-term, working, and long-term memory and a suite of tools to automate tasks, browse, schedule, email, and analyze documents.

Demonstrate data analysis through no-code prompt engineering techniques. See how prompts shape insights and streamline analysis workflows.

Explore a demo presentation that introduces core ideas in prompt engineering and AI, highlighting practical demonstrations within the certificate course.

Explore extracting information through prompt engineering and generative ai in a practical demo that highlights techniques for efficient data retrieval.

master resume quality checks using multi-shot prompting on google notebook, uploading documents or pasting text, rating technically on a 1–10 scale against job descriptions and samples to decide the cutoff.

Set up an automated feedback response workflow in Zapier using Google AI Studio Gemini, mapping form inputs, and generating replies. Publish by connecting Gmail to deliver the crafted reply.

Explore vibe coding with ChatGPT and Google AI Studio to build a functional English proficiency assessment and a tailored IDP.

Explore responsible and ethical AI, focusing on fairness, transparency, accountability, and privacy to prevent bias in hiring, loans, and healthcare.

Explore ethics, governance, and compliance as the foundation of responsible artificial intelligence, guiding values, risk assessments, transparency, and diverse perspectives to ensure lawful, accountable, and scalable artificial intelligence.

Explore the six pillars of ethical AI: bias and fairness, accountability, transparency and explainability, privacy and consent, safety and security, and sustainability, and their impact on responsible AI practices.

Apply ethics by design across data collection and deployment; use bias audits, SHAP and LIME, keep humans in the loop, ensure privacy with consent, and align with GDPR and CCPA.

Discover how prompt engineering drives generative AI by crafting structured prompts, applying modifiers and role-based modifiers, refining outputs with temperature and zero-shot strategies to generate novel text, images, or code.