Description
Intro to TensorFlow: The Foundation of Modern Deep Learning
Before Keras and high-level APIs, there’s **TensorFlow Core**—the engine that powers everything from Google Search to self-driving cars. This course teaches you the **fundamentals**: tensors, variables, sessions, graphs, and manual gradient computation—so you understand what’s *really* happening under the hood.
What You’ll Learn
- Tensors & operations—the building blocks of all TF programs
- Static computation graphs—TF 1.x style (still used in legacy systems)
- Variables and placeholders—managing state and input
- Manual gradient descent—compute and apply gradients by hand
- Debugging with tfdbg—inspect graph execution step-by-step
Why Learn Low-Level TensorFlow?
- Understand high-level APIs better—Keras, Estimators, tf.keras
- Debug production models—many enterprise systems still use TF 1.x
- Custom ops and kernels—required for research and optimization
Who Is This For?
- Engineers maintaining legacy TensorFlow codebases
- Researchers needing fine-grained control over computation
- Students studying classic deep learning implementations
- Interview prep for roles requiring TF internals knowledge
Don’t Just Use TensorFlow—Understand It
This course gives you the **mental model** to read, debug, and extend any TensorFlow system—past, present, or future.
Ready to go under the hood? Enroll now.
