Generative AI Certified Course

Course Description:

The  Generative AI course covers a wide range of topics, including Python programming, data science, AI, NLP, and advanced techniques in generative AI and prompt engineering. It includes interactive learning, projects, and assignments and aims to equip learners with the skills needed to excel in various AI-related roles.

Key Features of Course Divine:

• Collaboration with E‑Cell IIT Tirupati
• 1:1 Online Mentorship Platform
• Credit-Based Certification
• Live Classes Led by Industry Experts
• Live, Real-World Projects
• 100% Placement Support
• Potential Interview Training
• Resume-Building Activities

Career Opportunities After Generative AI:

• Generative AI Engineer
• Machine Learning Enginee
• AI Research Scientist
• Data Scientist
• AI Product Manager
• Prompt Engineer
• AI/ML Consultant
• NLP Engineer

Essential Skills you will Develop Generative AI: 

• Natural Language Processing
• Generative Models
• Prompt Engineering
• Multimodal AI
• Foundations of AI

Tools Covered:

• Programming & Development
• Python – Core language for AI/ML development
• Jupyter Notebook / Google Colab – For interactive experimentation and cod

• Pre-trained Model Libraries
• Hugging Face Transformers – Access to GPT, BERT, T5, and other generative models
• LangChain – Framework to build applications
• Model Deployment
• Gradio / Streamlit – Rapid prototyping of AI apps with UI
• Docker – Containerization for model deployment

Syllabus:

Module 1: Introduction to Generative AI What is Generative AI? History & evolution
Types of Generative AI models Applications across industries Overview of ethical concerns and challenges.

Module 2: Fundamentals of Machine Learning & Deep Learning Supervised, unsupervised & reinforcement learning Neural networks basics Backpropagation & gradient descent Introduction to deep learning frameworks.

Module 3: Natural Language Processing (NLP) Essentials Tokenization, stemming, lemmatization Language models and word embeddings Sequence-to-sequence models NLP datasets and tasks.

Module 4: Introduction to Transformer Models Attention mechanism Transformer architecture BERT, GPT, T5 overview Pre-training vs. fine-tuning.

Module 5: Generative Models in NLP GPT (Generative Pre-trained Transformers) Text generation with Chat GPT and similar models Prompt engineering basics Language-to-language & summarization models.

Module 6: Generative AI for Images and Audio GANs (Generative Adversarial Networks) Diffusion models (e.g., DALL·E,) Image-to-image, text-to-image generation Generative audio models (e.g., Jukebox, Voice Cloning).

Module 7: Prompt Engineering & Fine-tuning Prompt design techniques Zero-shot, few-shot learning Customizing GPT with fine-tuning Best practices and tools (Lang Chain.

Module 8: Tools and Platforms for Generative AI OpenAI (ChatGPT, DALL·E, Codex) Hugging Face Transformers Google Vertex AI, Amazon Bedrock  AutoML and Low-Code Tools.

Module 9: Real-World Use Cases & Projects Content generation (text, image, video)
Code generation and copilots AI for marketing, education, design Case studies from business & startups.

Module 10: Ethics, Regulations & Future of Generative AI Responsible AI and bias mitigation Copyright, IP & legal frameworks AI safety and governance Future trends in multimodal AI.

Industry Projects:

• Generative Models
• AI-Powered Art
• Personalized Learning Content
• AI for Financial Report Summarization
• Product Description
• Legal Document Generation

Who is this program for?

• Students & Recent Graduates
• Working Professionals
• Researchers & Academics
• Entrepreneurs & Innovators
• Digital Creators & Marketers
• Anyone Curious About AI

How To Apply

Mobile: 9100348679

Email: coursedivine@gmail.com