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Become AI-Ready: Deep Learning Fundamentals

LearnKartS via Coursera

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Overview

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Everyone talks about AI these days, but few people can actually explain how it works under the hood. This Deep Learning fundamentals course closes that gap by helping you learn how deep learning models are built, trained, & fixed when they get it wrong. The course consists of three modules. First Module traces Deep Learning's journey from a brain-inspired idea to the engine behind ChatGPT, hospital & financial domain. Second Module takes you inside a neural network, using TensorFlow Playground to watch a model learn through forward pass and backpropagation. And the last module gets into RNNs and LSTMs, the models that give AI a sense of memory, so it can follow language, speech, and Time Data. it's ideal for both beginners & experienced professionals looking to build practical AI skills. What makes this Deep Learning course different is that you won't just read about neural networks here. You'll watch them train, live, tied to real-world use cases in GenAI, healthcare, and finance. By the end, you'll have solid ground for advanced Deep Learning & Generative AI work. Enroll now and start building the AI foundation employers actually look for.

Syllabus

AI to Deep Learning: Foundations Behind Modern Intelligent Systems

This module builds the foundation of modern AI by explaining how deep learning evolved and why it powers today’s intelligent systems. You’ll understand how AI models learn from data and how neural networks were inspired by the human brain.

Inside Neural Networks: How Deep Learning Models Actually Learn

This module takes you inside neural networks to show how deep learning models actually learn using forward pass, parameters, and backpropagation. You’ll visually explore how models improve through training, errors, and optimization.

Sequence Intelligence: RNNs, LSTMs, and AI Memory Systems

This module introduces sequence intelligence and explains how AI systems handle time-based and language data using memory models. You’ll learn how RNNs and LSTMs enable AI to understand context, sequences, and long-term dependencies.