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AI+ Video™

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

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Self-Paced Online

USD $ 195.00

Instructor-Led Online

USD $ 1110.00

Overview What You'll Learn Certification Modules Certificates Industry Opportunities FAQ Prerequisites Exam Details Exam Blueprint Core Ai Tool Covered

At a Glance: Course + Exam Overview

Our training approach is human‑centred and outcomes‑driven. We focus on what learners can apply confidently.

What You'll Learn

AI-Enhanced Video Creation

Learn how to use machine learning and computer vision to automate editing, compositing, and content generation.

Intelligent Visual Effects

Understand how AI tools power motion tracking, object recognition, and real-time VFX integration in video production.

Generative Video Techniques

Explore how generative models create dynamic visuals, synthetic scenes, and AI-assisted storytelling.

Driven Storytelling

Discover how to analyze visual data and apply insights to craft more engaging and personalized video content.

End-to-End Workflow Integration

Master the use of AI across every stage of video production—from pre-visualization to post-production and distribution.

Certification Modules

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 YOLOv8 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

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

Finish the course and get certified

Industry Opportunities

AI Video Engineer

Develop intelligent video systems that enhance image quality, automate editing, and create adaptive, real-time visual experiences across platforms.

Video Data Scientist

Analyze visual data to build predictive models for content recommendation, scene recognition, and audience engagement optimization.

AI Motion Designer

Design AI-driven animations and effects, automate compositing and rendering, and produce dynamic visuals for films, games, and digital media.

Chief Video Innovation Officer (CVIO)

Lead the evolution of AI in visual media by driving innovation in intelligent production, personalized content, and next-generation video experiences.

Frequently Asked Questions

Can I apply what I learn in this course to real-world scenarios immediately?

Yes, you’ll gain hands-on experience with AI tools for video editing, visual effects, and content generation that can be immediately applied across industries like film, advertising, social media, and digital production.

What makes this course different from other Video and AI courses?

This course uniquely blends AI with video production, focusing on generative visuals, intelligent editing systems, and adaptive storytelling that redefine how video content is created, enhanced, and personalized.

What type of projects will I work on?

You’ll work on projects like AI-assisted video editing, automated scene detection, generative visual storytelling, and a capstone project focused on building an AI-powered video production tool or application.

How is the course structured to ensure I actually learn the skills?

The course integrates core theory with interactive hands-on, practical assignments, and real-world projects that help you apply AI in visual analysis, motion design, and intelligent video creation.

How does this course prepare me for the job market?

You’ll develop specialized AI and video technology skills that prepare you for roles such as AI Video Engineer, Motion Designer, Computer Vision Specialist, or Visual Content Strategist in film, media, and tech industries.

Prerequisites

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.

Exam Details

Passing Score

70%

Format

50 multiple-choice/multiple-response questions

Exam Blueprint

Foundations of AI in Video Integration	7%
Preparing Video Data for AI	15%
Machine Learning for Video Analysis	15%
Generative AI in Video	15%
Enhancing Video with AI	12%
Interactive and Immersive AI Video	12%
AI in Video Surveillance and Compliance	12%
Future of AI+ Video	12%