Certificate Course Prompt Engineering for Managers & Leaders

Discover how generative AI differs from traditional programming and neural networks, and how vibe coding with tools like Google AI Studio turns prompts into text, images, music, code, and apps.

Explore how ai agents act on behalf of users to achieve goals, making decisions and performing tasks automatically with tools like LangChain, Notion, and ChatGPT.

Large language models power generative AI by understanding and generating human language through NLP. They continually learn from massive data, enabling tasks like translation, summarization, coding, and creating original content.

Learn how AI hallucination in LLMs like ChatGPT produces false information, why it happens, and how to mitigate by sourcing, clarifying prompts, and cross-checking data.

Retrieval augmented generation combines a retriever and a language model to fetch external data and generate accurate, up-to-date answers using embeddings, vector databases, and orchestration frameworks like LangChain.

Explore what a prompt is for large language models like ChatGPT and learn how prompt engineering crafts clear, effective instructions to achieve high-quality AI results.

Learn to craft well-structured prompts by defining task, context, input data, and output format, using examples and audience tone to guide ai responses with clear, precise instructions.

Explore zero-shot, one-shot, and few-shot prompting techniques to guide generative ai for managers, enhance task performance, and balance speed with control through example-based instructions.

Learn how prompt modifiers shape ai output by guiding length, format, perspective, style, and audience; explore bullet points and other modifier types for managers and leaders.

Learn how AI models differ from fixed prompts, and master prompt control using tokens, temperature, top k, and top p to craft ChatGPT outputs.

Explore advanced prompting techniques used by prompt engineers, including chain-of-thought prompting, iterative prompting, and tree of thoughts, to enhance multi-step reasoning and strategic decision making for managers and leaders.

Explore how AI agents use an LLM brain, memory types (short term, long term, working memory), and a suite of tools to autonomously decide, act, and automate tasks for users.

Watch a practical demo of data analysis within a generative ai framework, illustrating how managers apply prompt engineering and ChatGPT techniques to analyze data.

Explore practical demonstrations of generative AI, prompt engineering, and ChatGPT for managers to harness intelligent decision making and team productivity.

Watch a demo-presentation on generative AI, prompt engineering, and ChatGPT for managers. Learn practical insights on applying these tools to streamline decision-making and collaboration.

Explore how managers use generative AI and prompt engineering with ChatGPT to extract information effectively, optimize decisions, and support strategic workflows.

Demo checks resume quality in Google Notebook using multi-shot prompting, with job descriptions and samples. Upload or paste resumes, then rate technically on a 1–10 scale.

Set up an automated feedback reply workflow in Zapier, using a form trigger and Gemini with system instructions to generate replies, then draft and send via Gmail.

Explore responsible and ethical AI, focusing on fairness, transparency, accountability, and privacy in real-world decisions like hiring, lending, and patient care.

Explore ethics, governance, and compliance as the foundation of responsible AI. Learn how governance translates values into action with risk assessments, transparency, and legal standards.

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

Practice ethical by design approaches in AI development, including bias audits, explainability tools, human in the loop, and impact assessments, to ensure privacy, consent, and regulatory compliance.

Explore how generative AI and prompt engineering drive content creation, personalization, and decision making by designing well structured prompts, using modifiers, and guiding ChatGPT and LLMs.