Generative AI Course
Master intelligent systems that generate text, images, code, and more — featuring Claude, DeepSeek, GPT-4 & frontier models.
industry focus: Anthropic Claude · DeepSeek · OpenAI · Hugging Face
Curriculum
Python for Generative AI▼
- Python Basics (Variables, Control Flow, Functions)
- Numpy, Pandas, Matplotlib, Seaborn
- Jupyter Notebooks / Google Colab
- Web scraping basics (for text data)
Introduction to AI & Generative AI▼
- What is AI, ML & Deep Learning
- Evolution and use-cases of Generative AI
- Types of Generative Models
- Overview of LLMs: Claude, DeepSeek, ChatGPT, LLaMA
- Introduction to tools like DALL·E, MidJourney, Claude Artifacts
Foundations of Machine Learning▼
- Supervised & Unsupervised Learning
- Linear & Logistic Regression
- Decision Trees, Random Forests
- Evaluation Metrics
- Feature Engineering & Preprocessing
Deep Learning Basics▼
- Introduction to Neural Networks
- Activation Functions
- Loss Functions and Optimizers
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Frameworks: TensorFlow & PyTorch
Generative Models▼
- What are Generative Models?
- Autoencoders (AE)
- Variational Autoencoders (VAE)
- Generative Adversarial Networks (GANs)
- Vanilla GAN, DCGAN, CycleGAN
- Use cases in image, video & audio generation
Introduction to Natural Language Processing (NLP)▼
- Text Preprocessing Techniques
- Tokenization, Lemmatization
- Word Embeddings: Word2Vec, GloVe
- Text Classification, Named Entity Recognition (NER)
- Sentiment Analysis
Large Language Models (LLMs) & Transformers▼
- Transformer Architecture & Attention Mechanism
- BERT, GPT, T5 overview
- Claude (Anthropic) & DeepSeek models: architecture, reasoning, API integration
- Fine-tuning LLMs for custom tasks
- Hugging Face Transformers library
Prompt Engineering & LLM APIs (ChatGPT, Claude, DeepSeek)▼
- Basics of Prompt Engineering
- Zero-shot, Few-shot, Chain-of-Thought prompting
- Using OpenAI ChatGPT / GPT-4, Claude API, and DeepSeek API
- Prompt templates for code, data, and reasoning tasks
- Building advanced agents with function calling
Multimodal Generative AI▼
- Image Generation with DALL·E, MidJourney, Stable Diffusion
- Audio & Video Generation Basics
- Text-to-Image pipelines
- Combining text, image, and voice inputs (Multimodal applications)
Real-World Projects▼
- AI Content Generator (Text + Image) with Claude & DALL·E
- Resume Analyzer & Cover Letter Generator using LLMs
- AI Chatbot powered by DeepSeek / GPT
- Generative AI for Marketing Automation
- Build your own RAG app with Claude & vector DB
Deployment & Integration▼
- Streamlit / Flask for UI
- Deploying Generative AI apps to cloud (Streamlit Cloud, Hugging Face Spaces)
- Using Vector Databases (FAISS, ChromaDB)
- RAG (Retrieval-Augmented Generation) pipelines
- CI/CD basics for AI apps (No Docker/AWS focus, simple cloud deployment)
Ethics, Risks & Future of Generative AI▼
- Copyright and plagiarism issues
- Deepfakes and misinformation risks
- Bias in AI-generated content
- Future trends and career paths in Generative AI
Deliverables▼
- Hands-on Mini Projects (Every 2-3 Modules)
- Capstone Project with Certificate
- Mock Interviews & Career Support
Course Details
Duration35 Weeks
Lessons60+
LevelBeginner to Advanced
CertificateYes
Tools & Technologies
Python
TensorFlow
PyTorch
OpenAI
Hugging Face
LangChain
DALL-E
Stable Diffusion
GPT-4
Claude (Anthropic)
DeepSeek
NumPy
Pandas
Scikit-learn
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