{"id":26349,"date":"2022-01-06T06:57:11","date_gmt":"2022-01-06T06:57:11","guid":{"rendered":"https:\/\/www.cloudthat.com\/training\/?post_type=stm-courses&p=26349"},"modified":"2026-09-18T11:37:14","modified_gmt":"2026-09-18T11:37:14","slug":"building-llm-applications-with-prompt-engineering","status":"publish","type":"stm-courses","link":"https:\/\/www.cloudthat.com\/training\/nvidia-certification-course\/building-llm-applications-with-prompt-engineering","title":{"rendered":"Building LLM Applications With Prompt Engineering"},"content":{"rendered":"

Note: This course has been retired and is no longer available. Please explore our latest NVIDIA courses<\/a> for updated training and certification options.<\/strong><\/p>\n

With the incredible capabilities of Large Language Models (LLMs), enterprises are eager to integrate them into their products and applications for use cases like text generation, large-scale document analysis, and chatbot assistants.<\/span>\u00a0<\/span><\/p>\n

The fastest way to begin leveraging LLMs is through prompt engineering, a foundational technique that underpins advanced methods such as Retrieval-Augmented Generation (RAG) and Parameter-Efficient Fine-Tuning (PEFT).<\/span>\u00a0<\/span><\/p>\n

In this instructor-led workshop, participants will work with NVIDIA\u2019s NIM deployment of Llama 3.1 alongside the popular\u00a0LangChain\u00a0library. Through practical, hands-on projects, learners will gain the skills to design, build, and deploy powerful LLM-based applications using prompt engineering.<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Note: This course has been retired and is no longer available. Please explore our latest NVIDIA courses for updated training and certification options. With the incredible capabilities of Large Language Models (LLMs), enterprises are eager to integrate them into their products and applications for use cases like text generation, large-scale document analysis, and chatbot assistants.\u00a0 […]<\/p>\n","protected":false},"author":5091,"featured_media":30997,"template":"","meta":{"footnotes":""},"stm_lms_course_taxonomy":[134],"metadata":{"stm_lms_product_id":["26350"],"_edit_lock":["1789733704:7038"],"_edit_last":["7038"],"permalink_customizer":["nvidia-certification-course\/building-llm-applications-with-prompt-engineering"],"permalink_customizer_regenerate_status":["1"],"_thumbnail_id":["30997"],"popular_course":["0"],"_popular_course":["field_64253688bc2e5"],"course_banner_image":[""],"_course_banner_image":["field_63c69a6b81cf1"],"mobile_banner_image":[""],"_mobile_banner_image":["field_63cf93896d207"],"banner_link":[""],"_banner_link":["field_63c69a9681cf2"],"banner_image":[""],"_banner_image":["field_621873548f922"],"banner_description":["Master Prompt Engineering with NVIDIA LLMs, LangChain, and Llama 3.1 to Build Scalable Generative AI Applications."],"_banner_description":["field_612c733ed3564"],"overview_section_heading":[""],"_overview_section_heading":["field_64538867ffdd0"],"after_completing_course_heading":["After completing this course, participants will be able to: "],"_after_completing_course_heading":["field_645c78ade3f50"],"after_completing_course_0_desciption":["Apply iterative prompt engineering best practices to create robust LLM applications."],"_after_completing_course_0_desciption":["field_6103ad2f9f5b2"],"after_completing_course_1_desciption":["Use LangChain to organize, compose, and optimize LLM workflows."],"_after_completing_course_1_desciption":["field_6103ad2f9f5b2"],"after_completing_course_2_desciption":["Write Python application code for generative tasks, document analysis, and chatbot development."],"_after_completing_course_2_desciption":["field_6103ad2f9f5b2"],"after_completing_course_3_desciption":["Build applications leveraging structured outputs from LLMs."],"_after_completing_course_3_desciption":["field_6103ad2f9f5b2"],"after_completing_course_4_desciption":["Develop and integrate LLM-powered agents capable of tool use and real-time data integration."],"_after_completing_course_4_desciption":["field_6103ad2f9f5b2"],"after_completing_course_5_desciption":["Deploy NVIDIA LLM NIM with Llama 3.1 for scalable enterprise-ready applications."],"_after_completing_course_5_desciption":["field_6103ad2f9f5b2"],"after_completing_course":["6"],"_after_completing_course":["field_6103aae828228"],"key_features_heading":["Key Features:"],"_key_features_heading":["field_645388ceffdd1"],"key_features_0_lists":["Gain hands-on prompt engineering experience by crafting and refining prompts to build applications for generation, analysis, and chatbots.\r\n\r\n "],"_key_features_0_lists":["field_6103ad559f5b3"],"key_features_1_lists":["Learn to build reusable LLM workflows with LangChain and efficiently deploy Llama 3.1 using NVIDIA NIM."],"_key_features_1_lists":["field_6103ad559f5b3"],"key_features_2_lists":["Apply your skills to real-world use cases such as document tagging, structured outputs, persona-driven chatbots, and tool integration."],"_key_features_2_lists":["field_6103ad559f5b3"],"key_features_3_lists":["

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Build practical skills through module-wise mini-projects and a final project integrating prompts, LangChain, structured outputs, and agentic tools.<\/p>\r\n\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n

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Earn an NVIDIA DLI certificate to validate your practical GenAI skills.<\/p>\r\n\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n

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  • Intermediate-level Python programming skills<\/li>\r\n \t
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