[MULTI] Applied Genai: Building Enterprise Topic Discovery Engines

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Applied Genai: Building Enterprise Topic Discovery Engines
Published 4/2026
Created by Marwan Gamal Hassan
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 20 Lectures ( 3h 0m ) | Size: 2 GB​

Master the Best of Both Worlds: Bridging Traditional NLP with State-of-the-Art Generative AI and Private LLMs.
What you'll learn
✓ Design and Deploy Local "Private" LLMs.
✓ Build automated topic discovery engines for business use cases.
✓ Merging Traditional Natural language processing with State-of-the-Art models and methods
✓ Implementing your own local efficient lightweight RAG
✓ Using "LLM-as-a-judge" for evaluation
Requirements
● Intermediate python Proficiency.
● Fundamental Machine Learning Knowledge.
● Familiarity with NLP Basics: While we will bridge the gap to modern methods, having the knowledge of what tokenization and "embeddings" are will help learners progress faster.
● familiarity with tools like langchain or llamaindex
● basic or some knowledge in RAG (Retrieval Augmented Generation)
Description
The world of Natural Language Processing (NLP) changed overnight with the rise of Large Language Models (LLMs). But for real-world engineering, simply sending data to a cloud API isn't enough. Modern industries demand privacy, cost-efficiency, and specialized accuracy.
In this project-based masterclass, you will learn to navigate the "Best of Both Worlds." You will master the transition from traditional NLP foundations to state-of-the-art Generative AI architectures. We don't just chase the hype; we build robust, hybrid systems designed for the 2026 tech landscape.
What makes this course different?
Most courses teach you how to use AI as a black box. This course pulls back the curtain. You will learn how to
• Own Your Models: Run Llama 3.2 and other state-of-the-art models locally using Ollama, ensuring 100% data privacy.
• Bridge the Gap: Combine the reliability of traditional statistical NLP with the reasoning power of modern Transformers.
What You Will Build
Through hands-on coding sessions, we will develop
• A Private Document Intelligence System using local LLMs.
• An Automated Topic Discovery Engine using BERTopic.
Is this for you?
If you are a Developer, Data Scientist, or Tech Lead who wants to stay ahead of the curve by mastering Local AI ecosystem and Hybrid Architectures, this is your roadmap. We move fast, we code clean, and we focus on what actually works in production.
Who this course is for
■ This course is designed for those who are tired of "surface-level" AI tutorials and want to master the bridge between traditional reliability and state-of-the-art innovation.
■ 1. The Aspiring AI Engineer You've learned the basics of Python and perhaps experimented with OpenAI's API, but you want to go deeper. You want to understand how to host, fine-tune, and optimize state-of-the-art models like Llama 3.2 on your own hardware. Goal: Move from "API Caller" to "Model Architect." 2. The Practical Data Scientist You are already working with data but find that traditional methods (like TF-IDF or basic Spacy) aren't enough for complex semantic tasks, while massive LLMs are too expensive or slow for your company's budget. Goal: Master Hybrid NLP-taking the "best of both worlds" to build efficient, high-performance engines. 3. The Enterprise Developer & Tech Lead You are responsible for building AI solutions that must respect data privacy and security. You cannot send sensitive company data to the cloud and need to implement local, quantized, and fine-tuned models. Goal: Implement private, local AI stacks that outperform generic cloud solutions in specialized domains like Finance or Healthcare. 4. The Researcher or Student in NLP You have a background in "Classic NLP" (GRUs, LSTMs, Word2Vec) and want to see how these fundamentals evolve into modern Siamese Networks and PEFT/QLoRA architectures. Goal: Upgrade your skill set to the 2026 industry standard without losing the foundational logic of the "traditional" world. This Course Is NOT For: Complete Programming Beginners: You should already be comfortable with Python. "Hype" Chasers: We won't just talk about what AI can do; we will roll up our sleeves and write the code to make it happen. Hardware Enthusiasts only: While we love GPUs, this course focuses on the Business Logic and Software Engineering behind the models.
■ Business leaders who want to integrate AI into their ecosystem
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