AI+ Video™

Target group

Video Creators and Editors: Professionals looking to integrate AI tools to automate editing, enhance visuals, and speed up production.

Filmmakers and Producers: Those aiming to explore intelligent video generation, virtual production, and data-driven storytelling.

Content Creators and Influencers: Individuals seeking to elevate their visual content with AI-powered creativity and personalized video experiences.

Designers and Animators: Creatives who want to merge motion design with AI-driven effects and smart visual enhancements.

Tech Enthusiasts and Innovators: Learners eager to understand how AI is transforming the future of video creation and media technology.

Course structure

Module 1: Foundation of AI in Video Integration

• 1.1 Basics of Video Processing
• 1.2 Introduction to AI in Video
• 1.3 Toolkits and Framework
• 1.4 Use Case: AI-enhanced Video Compression for Streaming Platforms
• 1.5 Case Study: YouTube’s AI-Driven Transcoding System

Module 2: Preparing Video Data for AI

• 2.1 Data Preparation for AI Models
• 2.2 Preprocessing and Augmenting Frames
• 2.3 Storage and Workflow Management
• 2.4 Use Case: Building AI-ready Video Datasets for Autonomous Driving Applications
• 2.5 Case Study: Tesla’s In-house Pipeline for Labeling Driving Scenarios across Multiple Geographies using Video Footage
• 2.6 Hands-On: Video Annotation using CVAT Tool, and Organizing them for Model Training

Module 3: Machine Learning for Video Analysis

• 3.1 Video Classification and Tagging
• 3.2 Object Detection and Movement Tracking
• 3.3 Action and Behavior Recognition
• 3.4 Use Case: Smart Surveillance Systems Detecting Abandoned Objects in Real Time
• 3.5 Case Study: Dubai Smart City’s AI Implementation for Object Recognition
• 3.6 Hands-On: Train YOLO on Sample Security Footage to Detect and Track Objects

Module 4: Generative AI in Video

• 4.1 Generating Synthetic Video with GANs
• 4.2 AI-Driven Animation and Avatars
• 4.3 Ethical Use of Generative Content
• 4.4 Use Case: Auto-Generation of Product Explainer Videos using Avatars and Synthesized Narration
• 4.5 Case Study: Synthesia’s Solution Enabling Businesses to Create AI-Driven Training and Marketing Videos
• 4.6 Hands-On: Generate a Deepfake or AI Avatar using AKOOL, and Explore Face Alignment and Identity Swapping

Module 5: Enhancing Video with AI

• 5.1 Super-Resolution and Restoration
• 5.2 Real-Time Video Enhancement
• 5.3 Making Video More Inclusive
• 5.4 Use Case: Streaming Platforms using AI to Enhance Resolution and Reduce Latency for Mobile Users.
• 5.5 Case Study: DeOldify’s Impact in Reviving Historical Video Archives by Upscaling and Colorizing Black-and-White Footage.
• 5.6 Hands-On: Use AI4Video to Enhance a Sample Low-Resolution Black-and-White Video and Visualize Improvement

Module 6: Interactive and Immersive AI Video

• 6.1 AI in AR and Mixed Reality
• 6.2 Intelligent Video Editing
• 6.3 Viewer Engagement & Adaptation
• 6.4 Use Case: Live Sports Broadcasters using AR to Overlay Player Stats during Gameplay
• 6.5 Case Study: NFL and AWS Collaboration to Deliver Real-Time Performance Insights via Augmented Visuals.
• 6.6 Hands-On: Creating a Highlight Video from a Video Clip using Clipchamp

Module 7: AI in Video Surveillance and Compliance

• 7.1 Security and Monitoring Systems
• 7.2 Automated Content Moderation
• 7.3 Addressing Privacy and Ethics
• 7.4 Use Case: Automated Real-Time Access Control in Corporate Offices Using Facial Authentication.
• 7.5 Case Study: Amazon Go’s Cashier-less Stores Using Computer Vision for Security and Consumer Behavior Tracking
• 7.6 Hands-On: Implement Facial Detection and Access Control Simulation using OpenCV and a Basic Recognition Model

Module 8: Future of AI+ Video Practitioner™

• 8.1 Trends and Emerging Technologies
• 8.2 AI Applications by Industry
• 8.3 Careers and Professional Growth

Certification

50 questions, 70% passing, 90 minutes, online proctored exam