Computer Programming in C#.NET and Databases (SQL)

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### Course Description: Prompt Engineering using Python and LLMs Unlock the power of Large Language Models (LLMs) with our beginner-friendly course, "Prompt Engineering using Python and LLMs." This course is designed to introduce you to the fundamentals of prompt engineering, equipping you with the skills needed to craft effective prompts and leverage the capabilities of LLMs for various applications. #### Course Objectives: - **Introduction to Prompt Engineering:** Understand the basics of prompt engineering and its significance in utilizing LLMs. - **Python for Prompt Engineering:** Learn essential Python programming skills tailored for prompt engineering tasks. - **Harnessing LLMs:** Discover how to use LLMs to generate, manipulate, and analyze text based on your crafted prompts. - **Practical Applications:** Apply your knowledge through hands-on projects and real-world scenarios to build practical solutions. #### Course Outline: 1. **Introduction to Prompt Engineering:** - What is prompt engineering? - Importance and applications of prompt engineering - Overview of Large Language Models (LLMs) and their capabilities 2. **Python Essentials for Prompt Engineering:** - Basic Python programming concepts - Key Python libraries for text processing - Setting up your development environment 3. **Crafting Effective Prompts:** - Understanding prompt structure and components - Techniques for creating clear and concise prompts - Examples of effective prompts for various tasks 4. **Interacting with LLMs:** - Introduction to popular LLMs (eg, GPT-3, GPT-4) - Using APIs to interact with LLMs - Generating text responses based on your prompts 5. **Advanced Prompt Techniques:** - Handling complex queries and multi-step instructions - Refining prompts for improved accuracy and relevance - Using prompts for different applications (eg, content generation, data analysis) 6. **Practical Projects:** - Building a text generation application - Creating a chatbot using prompt engineering techniques - Developing a data extraction tool using LLMs 7. **Ethical Considerations and Best Practices:** - Ensuring ethical use of LLMs and prompt engineering - Best practices for responsible AI development - Avoiding common pitfalls and challenges 8. **Future Directions and Further Learning:** - Exploring advanced topics in prompt engineering - Keeping up with the latest advancements in LLMs - Resources for continued learning and development #### Who Should Enroll: - Beginners with no prior experience in prompt engineering or LLMs - Individuals interested in learning Python programming - Aspiring AI enthusiasts looking to explore the potential of LLMs #### Prerequisites: - Basic computer literacy and familiarity with high school-level mathematics - No prior programming or AI experience required #### Race Outcomes: By the end of this course, you will be able to: - Understand the fundamentals of prompt engineering - Write and execute Python code for prompt engineering tasks - Create effective prompts to interact with LLMs - Develop practical applications using LLMs - Apply ethical considerations and best practices in your work Join us in "Prompt Engineering using Python and LLMs" to embark on your journey into the world of AI and prompt engineering. Gain the skills and confidence needed to create impactful solutions and unlock the full potential of Large Language Models.

This Python course teaches you the basics of programming in Python, including variables, data types, operators, control structures (if, for, while), functions, and lists. You will also learn how to manipulate data with libraries such as Pandas and NumPy, create graphs and visualizations with Matplotlib and Seaborn, and even develop simple web applications with Flask or Django.

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