Deep Learning with TensorFlow/Keras
Master deep learning from the ground up. Build real-world neural networks using TensorFlow/Keras and solve problems in vision, NLP, and AI product development.
Modules
- What is Deep Learning?
- Perceptron and Multilayer Perceptron (MLP)
- Activation Functions & Forward Propagation
- Loss Functions and Optimizers
- Tensor Operations and Graphs
- Keras Functional API vs Sequential API
- Model Building, Compilation, Fitting
- Callbacks, Checkpoints, and TensorBoard
- Convolution Layers & Pooling
- CNN Architectures: VGG, ResNet
- Image Augmentation
- Image Classification Project
- Overfitting & Dropout
- Batch Normalization
- Learning Rate Scheduling
- Early Stopping and Fine-tuning
- Recurrent Neural Networks (RNN)
- Long Short-Term Memory (LSTM)
- GRU and Bidirectional RNNs
- Time Series Forecasting Project
- Using Pre-trained Models (VGG16, Inception, MobileNet)
- Freezing vs Unfreezing Layers
- Transfer Learning for Image & Text
- Customizing Models with New Data
- Text Tokenization and Padding
- Embedding Layers
- Sentiment Classification Project
- Sequence-to-Sequence with LSTMs
- End-to-End DL Project Pipeline
- Model Deployment with Flask/Streamlit
- ONNX and TensorFlow Lite Conversion
- Productionizing Deep Learning Models
Industry Insights
95%
Industry Relevance
High
Market Demand
14 LPA+
Avg. Salary
Ready to start learning?
Your Learning Roadmap
Follow this path to mastery. Our AI guide leads the way.
DL Foundations
8 hrsPerceptrons, activations, optimizers, loss functions
TensorFlow & Keras
10 hrsAPIs, building, compiling, training models
CNN & Computer Vision
12 hrsImage models, augmentations, classification
Regularization & Tuning
10 hrsDropout, LR scheduling, fine-tuning
RNNs & Sequence Models
12 hrsRNN, LSTM, GRU, time-series
Transfer Learning
10 hrsVGG16, Inception, custom fine-tuning
NLP & Text Models
12 hrsEmbeddings, sentiment, seq-to-seq models
Projects & Deployment
10 hrsEnd-to-end DL pipeline, ONNX, cloud deploy
Why master Deep Learning with TensorFlow/Keras?
- Deep Learning powers AI breakthroughs, from GPT to self-driving cars.
- TensorFlow & Keras are the industry-standard tools used by Google, Meta, and startups alike.
- Gain hands-on experience building real neural networks from scratch, not just theory.
- You'll learn the math, architecture, and practical skills to deploy your own AI systems.
- This course is your gateway to research roles, LLM fine-tuning, and production-grade AI engineering.