🎨 Generative AI Tools & Workflows: Build, Create, and Automate with Intelligence

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🧾 Course Description

Generative AI is revolutionizing the way we create content, design experiences, and build intelligent systems. In “Generative AI Tools & Workflows”, you’ll explore how to use modern GenAI platforms — like OpenAI, HuggingFace, Google Vertex AI, and Stability AI — to generate text, images, code, and audio, and integrate them into real-world applications.

This course is designed for developers, creatives, product designers, marketers, and AI enthusiasts who want to master tools like ChatGPT, DALL·E, Midjourney, GitHub Copilot, and build end-to-end GenAI workflows that go beyond experimentation and into usable products.

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✅ Key Benefits

• 🧠 Understand GenAI Foundations — Learn how LLMs, diffusion models, and transformers work
• 🔌 Tool-Focused & Practical — Hands-on with OpenAI, HuggingFace, DALL·E, and more
• 🤖 Automate & Accelerate — Build GenAI agents, pipelines, and integrations
• 🧰 No-Code to Code — Combine GUI tools and APIs for flexible workflows
• 🚀 Real Use Cases — Product copywriting, code generation, image synthesis, voice AI, and chatbots

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🎯 Pre-requisites

• Basic knowledge of Python, APIs, and working with JSON
• Experience with web apps, automation, or creative tools is helpful
• No prior machine learning or deep AI background required

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📚 Curriculum Breakdown

📘 Module 1: Foundations of Generative AI

• What is Generative AI? Types: Text, Image, Code, Audio, Video
• Core models: LLMs (GPT), Diffusion (Stable Diffusion), GANs
• Understanding prompts, embeddings, transformers

💬 Module 2: Text Generation Workflows

• Prompt engineering with OpenAI GPT-4 / ChatGPT API
• Use cases: blog writing, summarization, email generation, chatbot flows
• Prompt chaining, few-shot examples, system messages

🎨 Module 3: Image Generation Tools

• Tools: DALL·E 3, Midjourney, Stable Diffusion, Canva AI
• Text-to-image prompts, styles, inpainting, variations
• Use cases: social media graphics, storyboarding, thumbnails

🧠 Module 4: Code Generation & Developer Tools

• Using GitHub Copilot, OpenAI Codex
• Generating Python/JavaScript snippets
• Automating documentation and test generation
• Safety and hallucination issues in generated code

🧩 Module 5: APIs, Agents, and Workflows

• Calling GenAI models via API (OpenAI, HuggingFace, Replicate)
• Building intelligent agents using LangChain or custom Python wrappers
• Connecting multiple tools into one pipeline (e.g., input → process → output → deploy)

🎛️ Module 6: Automation, Ethics & Limitations

• Using Zapier, Make, and no-code tools to trigger GenAI flows
• Handling latency, token limits, hallucination, cost
• Ethical considerations: bias, misuse, data privacy

🧪 Module 7: Final Projects (Choose One)

• Build a content generator for blogs/social media
• Create a prompt-based image+text portfolio builder
• Develop a simple AI chatbot using OpenAI API + LangChain
• Deploy a GitHub Copilot-style code assistant

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⏱️ Estimated Duration

Daily Study Time	Estimated Duration	Ideal For
2 hours/day	14–16 days (~2 weeks)	Explorers and builders
4 hours/day	6–8 days (1 week)	Balanced project-driven learners
6 hours/day	3–4 days (bootcamp)	Intensive fast-track learning

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🎓 Outcome

By the end of Generative AI Tools & Workflows, you will:

• Use text, image, and code generation tools effectively
• Integrate GenAI APIs into products and creative workflows
• Build simple agents and automation using OpenAI and LangChain
• Be ready to pursue LLM app development, GenAI product design, or AI agent engineering