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Kush Sharma

Welcome to AI Editing Projects for Beginners – Image & Video Use-Cases, your practical entry point into the exciting world of AI-powered image and video generation. This course is designed especially for beginners who want to see real, useful applications of the latest AI tools—not just theory.

Whether you’re a content creator, marketer, social media manager, or simply someone fascinated by the potential of AI, this course will show you how to leverage cutting-edge tools to create visually stunning content with ease.

What You’ll Learn

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Welcome to AI Editing Projects for Beginners – Image & Video Use-Cases, your practical entry point into the exciting world of AI-powered image and video generation. This course is designed especially for beginners who want to see real, useful applications of the latest AI tools—not just theory.

Whether you’re a content creator, marketer, social media manager, or simply someone fascinated by the potential of AI, this course will show you how to leverage cutting-edge tools to create visually stunning content with ease.

What You’ll Learn

Instead of giving you a generic tour of AI tools, this course focuses on real-world projects that walk you step-by-step through different creative challenges—just like how a pro would work.

In the introduction, you’ll understand the who, what, how, and why of this unique project-based format. You’ll also get a full list of tools we'll be using, along with downloadable resources to follow along.

Then, we dive right into five high-impact use-cases:

PROJECT #1 – Create an Ad for a Deodorant Brand

You’ll learn how to generate beautiful promotional visuals using Flux Kontext AI and do advanced product editing with Higgsfield AI Canvas. You’ll also discover why some tools like ChatGPT 4o might not always be the right fit for every project.

PROJECT #2 – Make a Video Commercial for an Energy Drink

Explore what "all-in-one" AI tools really mean. You’ll use OpenArt AI for inpainting and Higgsfield AI for mind-blowing visual effects. This section shows you how to blend multiple tools into a cohesive workflow.

PROJECT #3 – Build a Talking AI Avatar for a Multivitamin Brand

Combine four different reference images into one perfect avatar using OpenArt AI, and then bring it to life using HeyGen AI—creating a talking character with realistic facial expressions and emotions.

PROJECT #4 – Enhance an AI Image & Turn It Into a Video

Go a step further and make your AI-generated photos look more human-like using Enhancor AI, then animate them seamlessly with Kling AI.

PROJECT #5 – Conduct a Virtual Outdoor Photoshoot for a Lifestyle Coach

Learn how to use Higgsfield AI’s Character and Soul features to create incredibly realistic images, and then turn them into lifelike videos using VEO 3—without ever touching a camera.

Why This Course Stands Out

  • Beginner-friendly, no technical jargon

  • Real projects with clearly defined goals

  • Tool links, image downloads, and resources provided

  • Focus on storytelling and visual appeal

Finally, the course wraps up with extra tips, including how to access tools like VEO 3 for free, and where to go next in your AI editing journey.

If you’re curious about how AI is reshaping creativity—and you want to learn by doing—this is the perfect course to start with.

Let the robot take your hand, and step into the world of AI creation today.

Enroll now

What's inside

Learning objectives

  • Master the usage of the latest ai image and video tools by doing projects, even if you have never used ai tools before
  • Learn how to create professional-looking image and video ads using free ai tools.
  • Understand how to combine multiple ai tools to complete real-world creative projects.
  • Replace products in images and videos using inpainting and product swap ai features.
  • Generate realistic ai avatars and animate them with human-like expressions.
  • Learn how to get rid of that ai look in a portrait and make it look more realistic by adding texture on the skin
  • Learn how to add amazing visual effects to videos with a single click using ai
  • Learn about the future of image editing using ai tools like flux kontext
  • Learn about the future of video production and film-making by using amazing ai tools like kling ai and veo 3

Syllabus

Introduction to the Course
An Overview - The Who, What, How and Why of This Unique Course
The Image and Video AI Tools That You Will be Seeing in This Course
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Reading list

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Considered a classic textbook in the field of deep learning, this book provides the foundational knowledge required to understand the algorithms and architectures behind AI image generation models. It covers a broad range of topics in deep learning, offering mathematical and conceptual background essential for a deeper understanding. While not solely focused on image generation, it's a crucial reference for anyone serious about the underlying principles.
Offers a concise and accessible introduction to machine learning concepts. It covers fundamental topics that are prerequisites for understanding generative AI models used in image generation. It's a valuable resource for beginners or those needing a quick review of core machine learning principles before tackling more specialized topics.
This foundational textbook covering statistical techniques used in pattern recognition and machine learning. While published in 2006, its treatment of probabilistic models and Bayesian methods is highly relevant for understanding the theoretical underpinnings of many generative models. It's more valuable as a comprehensive reference for those with a strong mathematical background.
The third edition of this book explores Transformer architectures, which are increasingly relevant in multimodal models used for text-to-image generation. It covers concepts related to generative AI and includes applications with models like DALL-E 3. is useful for understanding the role of large language models in guiding image generation.
Explores the broader implications of AI on creativity, including in the visual arts. While not a technical guide, it provides valuable context on the intersection of AI and creative fields, which is highly relevant to AI image generation. It's a good supplementary read for understanding the cultural and philosophical aspects.
Provides a high-level overview of the AI landscape and its global implications. While not directly about AI image generation techniques, it offers important context on the rapid advancements and societal impacts of AI, including generative AI. It's a valuable read for understanding the broader forces driving the field.
Offers a critical perspective on the societal and environmental costs of AI. It delves into the infrastructure, labor, and data required for AI systems, including those used in image generation. It's an important read for understanding the ethical and political dimensions surrounding AI technology.
Is specifically focused on the models and techniques used for image generation, including VAEs, GANs, and diffusion models. It aims to provide both foundational concepts and practical techniques for creating images using AI. It highly relevant resource for understanding the core technical aspects of AI image generation.
Provides a practical, hands-on approach to understanding and implementing Generative Adversarial Networks (GANs). GANs have been a significant development in generative models and are relevant to understanding some of the historical and foundational techniques in AI image generation.
Offers a practical guide to using a popular AI image generation tool, Midjourney. While not deeply technical, it's highly relevant for users who want to understand how to effectively use these tools and the concept of prompt engineering. It provides step-by-step instructions and practical examples.
Offers a concise introduction to deep learning, suitable for readers with a STEM background. It covers fundamentals needed to understand landmark AI models relevant to image generation. It serves as a good starting point before delving into more specialized generative AI topics.
Explores the ethical implications of AI systems, a crucial aspect of AI image generation. It covers topics like integrity, moral decision-making, and design methodologies based on societal values. It's an important read for understanding the responsible development and use of AI in creative fields.
Provides a business perspective on generative AI, including its potential applications and implications. It can offer insights into how AI image generation is being viewed and adopted in professional contexts. It's suitable for those interested in the strategic and business aspects of the technology.
Focuses on prompt engineering, a critical skill for effectively using AI image generation tools. It provides practical guidance on crafting inputs to achieve desired outputs from generative models. This is highly relevant for users of tools like Midjourney and Stable Diffusion.
Offers a practical guide to implementing generative AI on a major cloud platform. While focused on AWS, it covers concepts relevant to building and deploying generative models, potentially including those for image generation. It's more for those interested in the practical implementation side.
Provides a broad exploration of generative AI, covering its history, capabilities, and future potential, including its role in AGI. It offers a wider perspective on the field beyond just image generation, which can be valuable for understanding the context and trajectory of the technology.
Provides a practical guide to image and video generation using TensorFlow. It covers techniques relevant to AI image generation and offers hands-on experience with a popular deep learning framework. It's a good resource for those who want to implement generative models.
Explores the intersection of AI and creativity through the lens of various art forms, including visual art. It delves into the history and potential of AI to create art, offering a broader cultural context for AI image generation. It's a good read for understanding the artistic implications.
Provides a comprehensive guide to AI for computer vision. While not exclusively focused on generative models, it covers fundamental computer vision concepts and techniques that are often utilized in AI image generation. It can serve as a useful reference for the computer vision aspects.
Provides a comprehensive introduction to generative AI models, including VAEs, GANs, and diffusion models, which are fundamental to AI image generation. It's a practical guide with examples using TensorFlow and Keras, making it suitable for those with a basic understanding of deep learning who want to dive into the creation of generative models. The second edition includes updated information on diffusion models like Stable Diffusion.

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