Certified Generative AI Engineer
Master GANs, LLMs, VAEs, and diffusion models in 8 weeks. Build real generative AI apps, fine-tune models, and earn a certified AI engineer credential.
Instructor
Cognovera
Category
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The Certified Generative AI Engineer program is an 8-week, project-based course designed to equip learners with the skills to design, train, and deploy state-of-the-art generative AI systems. Covering foundational AI concepts, GANs, VAEs, large language models (LLMs), and diffusion models, the course blends theory with hands-on projects to build real-world AI applications. Participants will learn prompt engineering, fine-tuning LLMs, creating AI-powered chatbots, generating synthetic media, and integrating models into applications—all while following ethical AI practices. By the end, learners will have a strong portfolio showcasing their generative AI expertise.
Week 1: Foundations of Generative AI & Python for AI
Week 2: Machine Learning & Deep Learning Essentials
Week 3: Introduction to Generative Models
Week 4: Generative Adversarial Networks (GANs)
Week 5: Large Language Models (LLMs)
Week 6: Advanced Generative AI Techniques
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26
Day 1: Variational Autoencoders (VAEs) – Theory & Implementation -
27
Day 2: Diffusion Models – Overview & Hands-on with Stable Diffusion
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28
Day 3: Multi-modal Generative AI – Text-to-Image, Text-to-Audio
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29
Day 4: Retrieval-Augmented Generation (RAG)
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30
Day 5: Project – AI-Powered Image Captioning
Week 7: Deployment & Ethics in Generative AI
Do I need prior AI/ML experience?
Basic ML knowledge is helpful, but the course covers all key prerequisites in the first two weeks.
Will I work on real projects?
Yes, every week has a mini project, plus a capstone project building a full generative AI application.
Which frameworks will I learn?
You’ll work with TensorFlow, PyTorch, Hugging Face, Stable Diffusion, and deployment tools like Streamlit or FastAPI.
Will I learn to fine-tune large language models?
Yes, you’ll practice prompt engineering, fine-tuning, and RAG-based applications.
What roles can I apply for after this course?
Generative AI Engineer, AI Application Developer, LLM Engineer, AI Research Associate, Creative AI Developer.
Skills You Will Learn
- Foundations of AI, deep learning, and neural networks
- Generative Adversarial Networks (GANs) & Conditional GANs
- Variational Autoencoders (VAEs)
- Diffusion models & Stable Diffusion applications
- Large Language Models (LLMs) & Hugging Face Transformers
- Prompt engineering & fine-tuning
- Multi-modal generative AI (text-to-image, image captioning, text-to-audio)
- Retrieval-Augmented Generation (RAG) techniques
- AI ethics, bias mitigation, and safety measures
- Deployment of AI models with Streamlit/FastAPI
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Course details
Lectures
40
Level
Intermediate
Basic info
- Course Name: Certified Generative AI Engineer
- Duration: 8 Weeks (5 Days/Week)
- Mode: Online / Classroom / Hybrid
- Level: Intermediate (basic Python knowledge recommended)
- Assessment: Weekly Mini Projects, Quizzes, Capstone Project
- Certification: Certified Generative AI Engineer
- Tools & Frameworks Covered: Python, TensorFlow, Keras, PyTorch, Hugging Face Transformers, Stable Diffusion, Streamlit/FastAPI
Course requirements
- Basic Python programming skills
- Familiarity with data handling libraries (NumPy, Pandas) is helpful
- Understanding of basic machine learning concepts recommended
- Computer with good internet and at least 8GB RAM (GPU access preferred)
Intended audience
- AI/ML engineers looking to specialize in generative AI
- Data scientists and researchers exploring advanced AI model building
- Developers interested in building AI-powered creative applications
- Professionals aiming to transition into cutting-edge AI roles
- Enthusiasts passionate about AI-generated media, text, and interactive apps
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