AI+ Video™
Embrace the future of AI in video to inspire innovation and craft immersive visual experiences
Certificate Code:
AP 7011
About This Course
- Beginner-Friendly Pathway: A perfect starting point for learners exploring AI-driven video creation, editing, and automation
- End-to-End Mastery: Covers AI video fundamentals, advanced tools, generative video workflows, and responsible content creation
- Industry-Aligned Skills: Understand how AI video technologies shape marketing, education, entertainment, and business communication
- Practical Execution: Provides guided exercises, templates, and workflows to help you produce professional-quality AI-powered videos confidently
Certificate Overview
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration
- Instructor-Led: 1 day (live or virtual)
- Self-Paced: 8 hours of content
Prerequisites
Basic Video Editing Skills, Understanding of AI Concepts, Familiarity with Data Analytics, Experience with Content Creation.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Course Modules
1
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
2
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
3
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
4
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
5
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
6
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
7
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
8
Module 8: Future of AI+ Video
- 8.1 Trends and Emerging Technologies
- 8.2 AI Applications by Industry
- 8.3 Careers and Professional Growth
AI Tools You'll Learn
TensorFlow
PyTorch
OpenCV
MediaPipe
Runway ML
Synthesia Studio
DeepFaceLab
Adobe Sensei
DaVinci Resolve Neural Engine
Runway
Pika Labs
Kaiber AI
DeepBrain AI Studio
NVIDIA Maxine SDK
Google Video AI API
FFmpeg Automation Tools
Unreal Engine with AI Plugins
Blender AI Add-ons
Stability Video Diffusion
