Course Description
Course curriculum
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1
Introduction to Prompt Engineering
- Course Introduction
- Brief on Generative Large Language Models
- What is Prompt Engineering
- Course Handouts (updated on 2024-12-18)
- Pros and Cons of Prompt Engineering
- Popular Platforms for Prompt Engineering
- Hands-on - Prompt Engineering with ChatGPT
- Quiz
- Reading Resources
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2
Prompt Engineering Patterns
- How to Write Good Prompts
- Key Elements of a Prompt
- What are Prompt Patterns
- Persona Pattern
- Flipped Interaction Pattern
- N-Shot Prompting Pattern
- Directional Stimulus Pattern
- Template Pattern
- Meta Language Pattern
- Brief on A Prompt Pattern Catalog
- Quiz
- Reading Resources
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3
Advanced Prompt Engineering Patterns
- Chain-of-Thought Pattern
- Self-Consistency Pattern
- Least-to-Most Pattern
- ReAct Pattern
- Other Popular Advanced Prompt Engineering Patterns
- Quiz
- Reading Resources
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4
Prompt Engineering Guidelines & Recommendations
- Best Practices for Constructing Prompts
- Generate Better Prompts Faster Automatically
- Optimize and Improve Prompts Automatically
- LLM API Pricing Awareness
- LLM Generation Parameters
- Choosing the Right LLM
- Quiz
- Reading Resources
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5
Prompt Engineering with Commercial LLM APIs
- Popular Commercial LLM API Platforms
- Hands-On: Prompt Engineering with OpenAI ChatGPT
- Hands-On: Prompt Engineering with Google Gemini
- Pros and Cons of Prompting with Commercial LLMs
- Quiz
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6
Prompt Engineering with Open-Source LLM APIs
- Popular Open-Source LLM API Platforms
- Hands-On: Prompt Engineering with Meta Llama 3.2 1B - HuggingFace
- Hands-On: Prompt Engineering with Meta Llama 3.2 90B - Groq
- Pros and Cons of Prompting with Open-Source LLMs
- Quiz
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7
Projects: Prompt Engineering with LLMs
- Introduction to Projects
- Prompt Engineering with GPT-4o Llama 3.2 on Real World Tasks - I
- Prompt Engineering with GPT-4o Llama 3.2 on Real World Tasks - II
- Multimodal Prompt Engineering with Google Gemini - I
- Multimodal Prompt Engineering with Google Gemini - II
- Multimodal Prompt Engineering with OpenAI GPT-4o - I
- Multimodal Prompt Engineering with OpenAI GPT-4o - II
- Project: Financial Report Analysis
- Course Conclusion
Who Should Enroll
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AI enthusiasts and beginners looking to get started with generative AI.
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Data scientists, developers, and researchers aiming to optimize AI performance.
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Educators and students curious about the transformative potential of AI in learning and problem-solving.
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Professionals in content creation, marketing, and automation seeking to enhance productivity with AI.
Key Takeaways
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Learn essential and advanced prompt patterns such as N-shot prompting, Chain-of-Thought, and ReAct to create highly optimized prompts tailored for diverse applications.
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Gain practical skills in leveraging commercial APIs (OpenAI GPT, Google Gemini) and open-source tools (HuggingFace, Grok Cloud) to implement real-world solutions.
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Understand and apply advanced techniques like token control, temperature tuning, and stop sequences to improve the precision, creativity, and relevance of AI responses.
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Develop a solid framework for comparing and selecting large language models (LLMs) based on factors like accuracy, cost, scalability, and infrastructure compatibility.
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Apply your learning through industry-focused projects involving multimodal inputs, agent workflows, and innovative applications, preparing you for professional use cases.
About the Instructor
Dipanjan Sarkar - Head of Community and Principal AI Scientist, Analytics Vidhya

FAQ
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What is Prompt Engineering?
Prompt Engineering is the art and science of crafting inputs (prompts) to optimize outputs from Large Language Models (LLMs). It involves techniques to guide models like GPT, Google Gemini, and Llama to generate high-quality and relevant responses.
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What are the benefits of learning Prompt Engineering?
By mastering Prompt Engineering, you can: 1. Enhance LLM performance for specific tasks. 2. Save costs by improving response accuracy. 3. Unlock advanced AI use cases across industries like education, marketing, and software development.
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What prior knowledge is required for this course?
While no specific technical expertise is mandatory, familiarity with AI concepts and basic Python skills can be beneficial. The course provides foundational guidance for beginners as well.
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Will I get a certificate of completion?
Yes, upon successfully completing the course and assessments, you will receive a verified certificate to showcase your expertise in Prompt Engineering.
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What industries can benefit from Prompt Engineering?
Prompt Engineering is versatile and can benefit industries like education, healthcare, customer service, marketing, and software development, enabling tailored AI applications in each domain.