| 1 - Project Blueprint Review Your Streamlined Pipeline.mp4 | 163.7 MB | ||
| 1 - Visualizing Sentiment and Preparing for Generative AI.mp4 | 151.1 MB | ||
| 1 - What you're going to get from this course.mp4 | 64.5 MB | ||
| 2 - Optimizing & Iterating on Your GenAI Pipeline (Part 1).mp4 | 123.2 MB | ||
| 2 - Preparing Data for Your Report.mp4 | 115.2 MB | ||
| 2 - What is Generative AI for Data Science.mp4 | 143.8 MB | ||
| 3 - Constructing Your AI-Powered Product Report (Core Content).mp4 | 104.9 MB | ||
| 3 - Responsible AI & Final Remarks.mp4 | 105.8 MB | ||
| 3 - The Power of Synthetic Data & Why Hugging Face.mp4 | 127.8 MB | ||
| 4 - Optimizing & Iterating on Your GenAI Pipeline (Part 2).mp4 | 127 MB | ||
| 4 - Outputting & Presenting Your E-commerce Analytics Report.mp4 | 115.4 MB | ||
| 4 - Setting Up & Loading Movie Review Data.mp4 | 90 MB | ||
| 4 -Prompt Engineering Techniques.url | 102.4 B | ||
| 5 - Automated Sentiment Analysis for Review Data.mp4 | 97.2 MB | ||
| 5 - Conclusion and Closing Statements.mp4 | 46.2 MB | ||
| 5 -6 types of AI content moderation and how they work.url | 102.4 B | ||
| 5 -Overview of Generative AI Principles.url | 102.4 B | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 19 total files | |||
Data Science with GenAI Analytics: Python + Hugging Face
https://WebToolTip.com
Published 9/2025
Created by Orants AI,Reza Mora
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 14 Lectures ( 1h 29m ) | Size: 1.53 GB
From Raw Data to AI-Powered Insights: Building Modern Analytics Pipelines with Python and Transformers
What you'll learn
Describe the core concepts of Generative AI and its role in enhancing data science workflows, including the generation of synthetic data.
Analyze unstructured text data using Hugging Face Transformers to perform sentiment analysis and extract key insights.
Design and implement a Python pipeline for data prep, sentiment analysis, and LLM summarization to generate and validate analytical reports programmatically.
Evaluate ethical considerations and best practices for responsible implementation of Generative AI in data science projects.
Requirements
Python programming fundamentals
Basic use of Jupyter notebooks or similar
Familiarity with AI language tools (e.g., understanding of what an LLM does)
Basic understanding of data structures and manipulation (pandas)
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