English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 23 lectures (2h 56m) | 2.21 GB
Cut the Noise, Build the AI: Learn GenAI Through Content Moderation, Trend Clustering, Custom Chatbots, and Retrieval
AI is transforming industries, but most people—even technical teams—don’t know how to truly control it. They rely on generic AI tools, struggle with limited customisation, and waste time on inefficient workflows.
The truth is, companies don’t just need people who can use AI. They need people who can shape it.
Fine-tuned AI is faster, cheaper, and more reliable than generic AI models.
Businesses that control their AI gain a competitive edge—reducing costs, improving accuracy, and keeping sensitive data in-house.
Right now, almost no one is teaching this. This course gives you an unfair advantage by bridging the gap between theory and real-world AI solutions.
What you’ll learn
- Create four practical AI projects—including chatbots, retrieval systems, trend analysis, and content moderation—that work in real-world scenarios.
- Skip the unnecessary theory and focus on the fastest way to get working, high-performing AI models.
- Go beyond basic AI usage—control AI behavior, integrate retrieval-augmented systems, and fine-tune models for specific business needs.
- Teach AI how to retrieve and use real knowledge, instead of relying on outdated model memory.
- Build an AI-powered moderation system that detects violations and improves content filtering with minimal human intervention.
- Learn how to cluster, filter, and interpret real-world social media trends with AI-driven analysis.
Table of Contents
AI-Powered Content Moderation Tool
1 Intro
2 Getting Started From Rules to Moderation Logic
3 Making Moderation Smart Adding AI to Detect Rule Violations
4 Enhancing Usability Building Reusable Functions for Moderation
5 Explain, Then Decide Prompt Strategies for Smarter Moderation
6 Closing the Loop Enhancing Moderation with Severity Scoring
Legal FAQ Chatbot (RAG System)
7 Introducing Retrieval-Augmented Systems and Embeddings
8 Retrieval in Action Matching Legal Questions with Provisions
9 Going Local Replacing APIs with Open-Source Models
10 Generating Locally Setting Up Llama On-Device
11 Smarter Search Improving Retrieval with Class-Based Filtering
Trend Analysis & Content Generation
12 Trend Analysis Preparing and Clustering Social Media Data
13 Exploring Trends Visualizing and Filtering Clusters for Insights
14 Real-Time Trends Generating Content That Engages
Fine-Tunning Specialised Chat-Bots
15 Introduction
16 The Fastest Way to Customize AI (and Why It’s Not Enough)
17 AutoTrain for Quick Fine-Tuning
18 Hardware for AI Training Options, Costs, and Trade-offs
19 Preparing Your Training Environment
20 Our First Fine-Tuning Teaching AI New Skills
21 Our First Fine-Tuning Part 2
22 Controlling AI Setting Boundaries in Training
Conclusion The Bigger Picture
23 Now You See the Whole Picture The Unfair Advantage
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