What You'll Learn
Comprehensive curriculum designed by industry experts
Neural Network Fundamentals
- Perceptrons
- Backpropagation
- Activation Functions
- Optimizers (Adam, SGD)
- Regularization
- Loss Functions
Computer Vision Architectures
- CNNs (Convolutional Neural Networks)
- ResNet
- YOLO/SSD for Object Detection
- Segmentation (U-Net)
- Transfer Learning
- Image Augmentation
Sequence Models
- RNNs & LSTMs
- GRU
- Attention Mechanism
- Transformers (BERT/GPT concepts)
- Time Series Forecasting
- Seq2Seq
Advanced Training
- Hyperparameter Tuning
- Distributed Training
- Mixed Precision Training
- Model Interpretability
- Deployment
- Research Paper Implementation
Live Projects
Build real-world applications that look great on your portfolio
Brain Tumor Detection
Build a CNN to detect tumors in MRI scans with high accuracy.
PyTorchMedical ImagingCNNFastAPI
Neural Style Transfer
Create an app that applies the artistic style of one image to another.
TensorFlowVGG19GradioPython
Prerequisites
- Strong Python
- Calculus/Linear Algebra basics
- ML fundamentals
Career Outcomes
- Build deep neural networks
- Read research papers
- Train models on GPUs
- Deploy DL models
Tools You'll Master
PyTorchTensorFlowJupyterGoogle Colab/KaggleWeights & Biases
Certification
Deep Learning Specialist Certificate
Performance-based stipend
Apply for This Internship
Start your journey with Deep Learning & Neural Networks Internship