Description
Deep Learning with TensorFlow & Keras: From Theory to Production
TensorFlow and Keras have become the de facto standard for deep learning in industry—used by Google, NVIDIA, and thousands of startups. This course cuts through the noise and teaches you to build, train, and deploy real-world models: image classifiers, time-series predictors, chatbots, and even AI-generated art.
What You’ll Build
- A handwritten digit recognizer using dense and convolutional networks
- A movie sentiment analyzer with recurrent neural networks (RNNs)
- A GAN that generates new human faces
- A time-series forecaster for stock or weather data
- A REST API to serve your model using Flask and TensorFlow Serving
Core Concepts Covered
- TensorFlow 2.x fundamentals—eager execution, tf.data, GradientTape
- Keras high-level API—Sequential, Functional, and Model subclassing
- Model debugging & visualization—TensorBoard, activation maps, weights inspection
- Transfer learning—fine-tuning ResNet, VGG, and BERT for your domain
- Deployment strategies—TensorFlow.js, TensorFlow Lite, and cloud APIs
Why This Matters in 2025
Companies don’t just want deep learning hobbyists—they want engineers who can **ship models that solve business problems**. This course bridges that gap with production-grade code, error handling, and performance optimization.
Who Should Enroll?
- Python developers entering AI
- Data scientists moving from scikit-learn to deep learning
- Researchers needing a robust, scalable framework
- Students building capstone projects
Your AI Toolkit Starts Here
You’ll graduate with a portfolio of deployable models—and the confidence to tackle any deep learning challenge.
Stop watching tutorials. Start shipping AI. Enroll today.
