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Details for:
Coursera | NVIDIA: Prompt Engineering And Data Analysis
coursera nvidia prompt engineering data analysis
Type:
Other
Files:
21
Size:
379.4 MB
Uploaded On:
March 9, 2025, 8:05 p.m.
Added By:
Prom3th3uS
Seeders:
2
Leechers:
2
Info Hash:
389F74F2479850D3E2E29203EBAE3FAE85376661
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Visit >>> http://onehack.us/ https://i.ibb.co/tM6XyBY8/hghytr.png Coursera - NVIDIA: Prompt Engineering and Data Analysis Course details NVIDIA: Prompt Engineering and Data Analysis is the fifth course of the Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs - Associate Specialization. This course equips learners with a solid foundation in prompt engineering, data analysis, and visualization techniques for optimizing Large Language Models (LLMs). The course covers essential concepts such as prompt engineering fundamentals, effective prompt creation, and P-tuning for enhanced LLM performance. It also delves into techniques for analyzing text data, different plot types, and their role in effective data visualization. Learners will gain hands-on experience with tools like NVIDIA NeMo for prompt engineering and cuDF and Dask cuDF for accelerated data analysis workflows. The course is divided into two modules with Lessons and Video Lectures. Learners will engage in approximately 3:00-3:30 hours of video content, covering both theoretical concepts and practical applications. Each module is paired with quizzes to assess understanding and reinforce learning. Module 1: Foundations of Prompt Engineering Module 2: Data Analysis and Visualization By the end of this course, learners will be able to: - Understand prompt engineering and its role in LLM optimization. - Apply P-tuning and RAG architecture for improved model performance. - Utilize data analysis and visualization techniques for effective NLP tasks. This course is ideal for learners interested in enhancing their skills in prompt engineering and data analysis for LLM optimization, with a focus on practical implementation. What you'll learn - Understand prompt engineering and its role in LLM optimization. - Apply P-tuning and RAG architecture for improved model performance. - Utilize data analysis and visualization techniques for effective NLP tasks. There are 2 modules in this course NVIDIA: Prompt Engineering and Data Analysis is the fifth course of the Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs - Associate Specialization. This course equips learners with a solid foundation in prompt engineering, data analysis, and visualization techniques for optimizing Large Language Models (LLMs). The course covers essential concepts such as prompt engineering fundamentals, effective prompt creation, and P-tuning for enhanced LLM performance. It also delves into techniques for analyzing text data, different plot types, and their role in effective data visualization. Learners will gain hands-on experience with tools like NVIDIA NeMo for prompt engineering and cuDF and Dask cuDF for accelerated data analysis workflows. The course is divided into two modules with Lessons and Video Lectures. Learners will engage in approximately 3:00-3:30 hours of video content, covering both theoretical concepts and practical applications. Each module is paired with quizzes to assess understanding and reinforce learning. Module 1: Foundations of Prompt Engineering Module 2: Data Analysis and Visualization By the end of this course, learners will be able to: - Understand prompt engineering and its role in LLM optimization. - Apply P-tuning and RAG architecture for improved model performance. - Utilize data analysis and visualization techniques for effective NLP tasks. This course is ideal for learners interested in enhancing their skills in prompt engineering and data analysis for LLM optimization, with a focus on practical implementation. General Details: Duration: 1h 9m Updated: 03/2025 Language: English Source: https://www.coursera.org/learn/nvidia-prompt-engineering-and-data-analysis Instructor: https://www.whizlabs.com/ MP4 | Video: AVC, 1920x108p | Audio: AAC, 44.100 KHz, 2 Ch
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01-Foundations_Of_Prompt_Engineering/00.Support - Onehack.Us.txt
94 bytes
01-Foundations_Of_Prompt_Engineering/01-welcome_to_the_course_instructions.html
11.2 KB
01-Foundations_Of_Prompt_Engineering/02-overview_of_foundations_of_prompt_engineering_instructions.html
2.8 KB
01-Foundations_Of_Prompt_Engineering/03-prompt_engineering.mp4
23.5 MB
01-Foundations_Of_Prompt_Engineering/04-fundamentals_of_prompt_design.mp4
18.7 MB
01-Foundations_Of_Prompt_Engineering/05-techniques_for_effective_prompts.mp4
19.9 MB
01-Foundations_Of_Prompt_Engineering/06-prompt_efficient_finetuning_technique.mp4
26.0 MB
01-Foundations_Of_Prompt_Engineering/07-prompt_learning_p_tuning.mp4
19.8 MB
01-Foundations_Of_Prompt_Engineering/08-introduction_to_nvidia_nemo.mp4
24.1 MB
01-Foundations_Of_Prompt_Engineering/09-prompt_engineering_demo_with_an_llm.mp4
22.2 MB
01-Foundations_Of_Prompt_Engineering/10-understanding_rag_architecture_of_llm.mp4
28.9 MB
02-Data_Analysis_And_Visualization/01-overview_of_data_analysis_and_visualization_instructions.html
2.7 KB
02-Data_Analysis_And_Visualization/02-techniques_of_text_data_analysis.mp4
33.3 MB
02-Data_Analysis_And_Visualization/03-text_data_visualization_demo.mp4
49.6 MB
02-Data_Analysis_And_Visualization/04-types_of_plot_and_its_importance.mp4
37.3 MB
02-Data_Analysis_And_Visualization/05-data_visualization_for_structured_data_demo.mp4
40.0 MB
02-Data_Analysis_And_Visualization/06-accelerated_data_analysis_workflow_with_cudf_and_dask_cudf.mp4
31.6 MB
02-Data_Analysis_And_Visualization/07-exam_tips_data_visiualization_techniques_for_text_data.mp4
4.6 MB
02-Data_Analysis_And_Visualization/08-key_takeaways_of_the_course_instructions.html
2.4 KB
02-Data_Analysis_And_Visualization/09-course_conclusion_instructions.html
2.1 KB
Support - Onehack.Us.txt
94 bytes