AI+ Video Practitioner™

Course code: NPAP7011

Formerly known as AI+ Video™

Embrace the future of AI in video to inspire innovation and craft immersive visual experiences

  • Entry-Level Learning Path: An ideal introduction for those discovering AI-based video production, editing, and streamlining.
  • Comprehensive Skill Acquisition: Encompasses AI video essentials, sophisticated tools, generative video processes, and ethical content development
  • Market-Ready Capabilities:Learn AI video tech's influence on marketing, learning, entertainment, and corporate messaging.
  • Action-Based Implementation: Supplies directed tasks, templates, and processes to confidently generate pro-level AI-enhanced videos.

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date
Place
Type Course
duration
Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

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.

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

Prerequisites

  • Video Editing Foundations: Experience with video editing applications is required.
  • AI Principles Awareness: Elementary understanding of artificial intelligence fundamentals
  • Data Analytics Background: Competence with data-informed strategies and evaluation
  • Digital Media Production: Practical background in creating multimedia content

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