Prompt Engineering Masterclass with GPT-5 & Copilot

Learning outcome:

After this course, learners (students, jobholders or corporate employees, freelancers, business owners) from any background will be able to use AI to enhance their productivity to reach the highest level in their own professional field through only simple prompts.

Who can buy this course:

1. Students from any background who want to prepare for the future job marketplace and wants stay ahead than others.

2. Professional job holders from any background who want to make their job tasks easy and want to become the most efficient employee.

3. Business owners who want to set an efficient workflow to increase business productivity.

4. Aspiring freelancers who want to land remote AI related jobs (LLM, SLM, training AI models).

5. Corporate employees & managers who want to set automated workflow to develop processes and projects.

6. Those who have realized the inevitable take over in the job market by AI, but are unsure where to start.

Course Summary:

Section 1: Foundation of Prompt Engineering & Microsoft Copilot: This section introduces learners to the fundamentals of prompt engineering and its role in shaping AI outputs. It begins with an overview of why prompts matter, emphasizing that the way instructions are framed directly impacts the accuracy, creativity, and usefulness of responses. Learners are then guided through an understanding of Microsoft Copilot—its integration across platforms, its ability to interpret natural language, and its role as both a productivity tool and a learning partner. The section also covers key principles of prompt engineering, such as clarity, specificity, contextual awareness, and iterative refinement. Finally, it introduces three core prompting strategies: zero-shot prompting, where no examples are given; few-shot prompting, where a handful of examples guide the AI; and multi-shot prompting, where multiple examples establish strong patterns for complex or consistent outputs.

Section 2: Crafting effective prompts: This section dives deeper into the art of designing prompts that consistently yield high-quality results. It begins with prompt structure and clarity, showing how well-formed instructions reduce ambiguity and improve precision. Learners then explore how to leverage examples and templates to guide Copilot toward specific tones, formats, or workflows. Parameter tuning is introduced as a way to adjust variables—such as length, style, or level of detail—to refine outputs for different contexts. The section concludes with iterative refinement, teaching learners how to test, evaluate, and adjust prompts in cycles until the desired outcome is achieved. This hands-on approach ensures learners develop a practical skillset for adapting prompts to real-world needs.

Section 3: Advanced Techniques with Copilot: Here, learners move beyond the basics into advanced strategies that unlock Copilot’s full potential. The section begins with chain-of-thought prompting, where users guide Copilot through step-by-step reasoning to improve logical accuracy and transparency. It then introduces context enhancement through embeddings and few-shot prompting, showing how vector databases can be used to supply Copilot with richer, domain-specific knowledge. Prompt chaining and orchestration are also covered, teaching learners how to break down complex tasks into multiple Copilot calls and coordinate them into seamless workflows.

Section 4: Real - World Applications and Case Studies: This section grounds theory in practice by showcasing how prompt engineering can be applied across industries. In customer support, learners see how dynamic prompts can be designed for chatbots and support agents that adapt to user inputs in real time. The section demonstrates a live project through generating a professional complete business analysis and sales performance report of an e-commerce company through a single iterative deep research prompt.