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Total Size:
379.4 MB
Info Hash:
389F74F2479850D3E2E29203EBAE3FAE85376661
Added By:
Added:
April 21, 2026, 10:54 a.m.
Stats:
|
(Last updated: April 21, 2026, 10:55 a.m.)
| File | Size |
|---|---|
| 00.Support - Onehack.Us.txt | 94 bytes |
| 01-welcome_to_the_course_instructions.html | 11.2 KB |
| 02-overview_of_foundations_of_prompt_engineering_instructions.html | 2.8 KB |
| 03-prompt_engineering.mp4 | 23.5 MB |
| 04-fundamentals_of_prompt_design.mp4 | 18.7 MB |
| 05-techniques_for_effective_prompts.mp4 | 19.9 MB |
| 06-prompt_efficient_finetuning_technique.mp4 | 26.0 MB |
| 07-prompt_learning_p_tuning.mp4 | 19.8 MB |
| 08-introduction_to_nvidia_nemo.mp4 | 24.1 MB |
| 09-prompt_engineering_demo_with_an_llm.mp4 | 22.2 MB |
| 10-understanding_rag_architecture_of_llm.mp4 | 28.9 MB |
| 01-overview_of_data_analysis_and_visualization_instructions.html | 2.7 KB |
| 02-techniques_of_text_data_analysis.mp4 | 33.3 MB |
| 03-text_data_visualization_demo.mp4 | 49.6 MB |
| 04-types_of_plot_and_its_importance.mp4 | 37.3 MB |
| 05-data_visualization_for_structured_data_demo.mp4 | 40.0 MB |
| 06-accelerated_data_analysis_workflow_with_cudf_and_dask_cudf.mp4 | 31.6 MB |
| 07-exam_tips_data_visiualization_techniques_for_text_data.mp4 | 4.6 MB |
| 08-key_takeaways_of_the_course_instructions.html | 2.4 KB |
| 09-course_conclusion_instructions.html | 2.1 KB |
| Support - Onehack.Us.txt | 94 bytes |
Name
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379.4 MB
[31
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2]
2026-04-21
| Uploaded by Prom3th3uS | Size 379.4 MB | Health [ 31 /2 ] | Added 2026-04-21 |
NOTE
SOURCE: Coursera | NVIDIA: Prompt Engineering And Data Analysis
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MEDIAINFO
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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