Course Overview
TOPThe AI+ Video Practitioner™ course provides an in-depth, instructor-led exploration of AI-powered video processing, analysis, and generation. The curriculum covers foundational video processing, dataset preparation, object detection, action recognition, generative video models, AR/VR overlays, and automated compliance systems. Participants work directly with tools like YOLOv8, CVAT, OpenCV, and AI4Video to build intelligent video pipelines. Industry case studies from YouTube, Tesla, Dubai Smart City, and Amazon Go demonstrate enterprise-grade implementations. The course equips professionals with technical skills needed to deploy and optimize AI-driven video systems across sectors.
Scheduled Classes
TOP| 07/29/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 08/26/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 09/30/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 10/28/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 11/25/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 12/23/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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What You'll Learn
TOP- Understand the fundamentals of video processing and AI-based visual analysis
- Build ML and deep learning models for object detection, tracking, classification, and behavior recognition
- Apply generative AI techniques to create synthetic video, avatars, and animation
- Enhance video quality using AI-driven restoration, noise reduction, and super-resolution tools
- Develop intelligent video pipelines for AR overlays, security systems, compliance, and automation
Outline
TOPFoundation of AI in Video Integration
- Basics of Video Processing
- Introduction to AI in Video
- Toolkits and Framework
- Use Case: AI-enhanced Video Compression for Streaming Platforms
- Case Study: YouTube’s AI-driven Transcoding System Automatically Optimizes Video Quality based on Device and Internet conditions
Preparing Video Data for AI
- Data Preparation for AI Models
- Preprocessing and Augmenting Frames
- Storage and Workflow Management
- Use Case: Building AI-ready Video Datasets for Autonomous Driving Applications
- Case Study: Tesla’s In-house Pipeline for Labeling Driving Scenarios across Multiple Geographies using Video Footage
- Hands-On: Video Annotation using CVAT Tool, and Organizing them for Model Training
Machine Learning for Video Analysis
- Video Classification and Tagging
- Object Detection and Movement Tracking
- Action and Behavior Recognition
- Use Case: Smart Surveillance Systems Detecting Abandoned Objects in Real Time
- Case Study: Dubai Smart City’s AI Implementation for Object Recognition and Suspicious Behavior Detection in Public Transport Hubs
- Hands-On: Train YOLOv8 on Sample Security Footage to Detect and Track Objects
Generative AI in Video
- Generating Synthetic Video with GANs
- AI-Driven Animation and Avatars
- Ethical Use of Generative Content
- Use Case: Auto-Generation of Product Explainer Videos using Avatars and Synthesized Narration
- Case Study: Synthesia’s Solution Enabling Businesses to Create AI-driven Training and Marketing Videos in Multiple Languages.
- Hands-On: Generate a Deepfake or AI Avatar using AKOOL, and Explore Face Alignment and Identity Swapping
Enhancing Video with AI
- Super-Resolution and Restoration
- Real-Time Video Enhancement
- Making Video More Inclusive
- Use Case: Streaming Platforms using AI to Enhance Resolution and Reduce Latency for Mobile Users.
- Case Study: DeOldify’s Impact in Reviving Historical Video Archives by Upscaling and Colorizing Black-and-White Footage.
- Hands-On: Use AI4Video to Enhance a Sample Low-Resolution Black-and-White Video and Visualize Improvement
Prerequisites
TOPRequired
- Basic Video Editing Skills: Familiarity with video editing software is essential
- Understanding of AI Concepts: Basic knowledge of artificial intelligence principles
- Familiarity with Data Analytics: Comfort with data-driven decision-making and analysis
- Experience with Content Creation: Hands-on experience in producing digital media
