AI and ML
Data Ingestion with SQL, Pandas DataFrames, Interactive Visualization with Matplotlib/Seaborn, Supervised Learning with Scikit-learn, K-Nearest Neighbors & Decision Trees, Fraud Detection Pipeline, PyTorch Fundamentals, Neural Networks & Backpropagation, CNNs with Transfer Learning, Image Classification on CIFAR-10, NLP Tokenization, Hugging Face Transformers, Sentiment Analysis Chatbot, PyTorch Deep Learning Models, LangChain & Prompt Engineering, RAG with Pinecone Vector DB, Document Q&A System, End-to-End Project Deployment, Streamlit & Docker, GitHub Portfolio
Master the skills to turn raw data into powerful AI-driven insights and solutions. Build predictive models for real-world applications like fraud detection, sentiment analysis, and image classification, using industry-leading tools such as Python, PyTorch, TensorFlow, SQL, Scikit-learn, Pandas, Matplotlib, and Hugging Face. Work with supervised/unsupervised learning, explore key algorithms like K-Nearest Neighbors, Decision Trees, and CNNs, Transformers, and integrate SQL queries with interactive data visualizations. By the end of the program, you’ll have designed, trained, and deployed your own AI projects—covering the full lifecycle from data ingestion to cloud deployment—while ensuring performance, scalability, and real-world applicability in the global tech ecosystem.
