AI & Machine Learning
Master Artificial Intelligence from the fundamentals to advanced deep learning, including neural networks, data processing, model building, optimization, and real-world AI project deployment.
Master Artificial Intelligence from the fundamentals to advanced deep learning, including neural networks, data processing, model building, optimization, and real-world AI project deployment.
A structured, hands-on AI & ML program that covers math fundamentals, machine learning, deep learning, and real deployment—everything you need to become an AI engineer.
Supervised, unsupervised, regression, classification, clustering, probability & statistics.
Neural networks, CNNs, RNNs, LSTMs, transformers and modern AI architectures.
Image classification, NLP models, chatbots, recommendation engines, automation scripts.
Model optimization, containerization, cloud deployment, monitoring & CI/CD workflows.
A complete hands-on roadmap into modern AI and ML engineering.
Linear algebra, calculus, statistics, probability, matrices & metrics.
Data cleaning, EDA, feature engineering, pipelines, normalization.
Regression, classification, trees, random forests, SVMs, clustering.
ANN, CNN, RNN, LSTM, transformer models using TensorFlow & PyTorch.
Custom model training, tuning, augmentation, GAN basics & evaluation.
Model serving using FastAPI, Docker, cloud environments & MLOps basics.
Learn to work with industry-standard AI tools, libraries & frameworks.
Python
TensorFlow
PyTorch
Jupyter
Docker
Python
TensorFlow
PyTorch
Jupyter
Docker
A flexible, project-based AI course designed for real-world engineering roles.
Instructor-led training + weekly projects & assessments.
No prior ML knowledge required, we teach from fundamentals.
Deploy a real ML model (vision, NLP, or automation) with documentation.
Official certificate + portfolio-ready project documentation.
Answering the most common student queries.