Artificial Intelligence & Machine Learning Program
From Python Foundations to Real-World AI Projects
🔹 Python for Artificial Intelligence
- Python fundamentals for AI & ML
- NumPy, Pandas, Matplotlib, Seaborn
- Data handling, preprocessing & visualization
🔹 Machine Learning with Python
- Supervised & Unsupervised Learning
- Regression, Classification & Clustering
- Decision Trees, Random Forests, XGBoost
- Model evaluation & performance tuning
🔹 Deep Learning
- Neural Networks fundamentals
- TensorFlow & PyTorch basics
- CNNs for Image Processing
- RNNs & LSTMs for Sequence Data
🔹 Generative AI & Large Language Models (LLMs)
- Introduction to Generative AI
- Transformers & Attention Mechanism
- Prompt Engineering techniques
- Working with OpenAI / LLM APIs
- Chatbots & AI Assistants with Python
🔹 Natural Language Processing (NLP)
- Text preprocessing & embeddings
- Sentiment Analysis & Text Classification
- Named Entity Recognition (NER)
- Language Translation & Summarization
🔹 Computer Vision
- Image processing with OpenCV
- Face Detection & Recognition
- Object Detection (YOLO / SSD)
- Image Classification Projects
🔹 AI Tools & Frameworks
- Scikit-learn, TensorFlow, PyTorch
- Hugging Face Transformers
- LangChain & Vector Databases (FAISS, Pinecone)
🔹 MLOps & Deployment
- Model deployment using Flask / FastAPI
- Streamlit dashboards
- Docker basics for AI apps
- Model versioning & monitoring
🔹 Real-World AI Projects
- End-to-end AI project development
- Industry use-case–based assignments
- Capstone Project (Resume Ready)
🔹 Career & Interview Preparation
- AI & ML interview questions
- Resume & LinkedIn optimization
- Portfolio building with GitHub
- Mock interviews & case studies
