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Taught in Stage 2
Last Updated: August 2026
Prompt Engineering
Techniques for reliably controlling LLM outputs.
Overview
Prompt engineering is the practice of designing and refining inputs (prompts) to effectively communicate with large language models. It involves techniques like few-shot prompting, chain-of-thought, and structural formatting to elicit accurate, reliable, and safe responses.
Why Learn This in 2026?
As models become more capable, the skill of guiding them effectively becomes more nuanced. True prompt engineering isn't just writing text; it involves systemic evaluation, guarding against injections, and ensuring structured JSON outputs for application integration.
How We Teach This
Module 11 & 12: Modern LLMs & Practical Engineering
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Market Trajectory
Evolving rapidly
Moving from manual prompt writing to programmatic prompt optimization and evaluation (DSPy).
- A highly valued skill in both technical and non-technical roles.
Hiring Landscape
Demand LevelHigh
Typical Salary Impact₹8L - ₹20L+ (India)
Top Employers Seeking This
AI ConsultanciesEnterprise AI teams
Ready to master Prompt Engineering?
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