What careers can I pursue after learning deep learning basics?

This course helps you prepare for entry-level and intermediate roles such as AI Engineer, Machine Learning Engineer, Data Scientist, and AI Product positions. It also lays solid groundwork before diving into niche topics such as Generative AI.

Does this course cover Generative AI?

This course details the deep learning mechanisms that underlie generativeAI and introduces the underlying concepts such as neural networks and sequence learning. It is not specifically about GenAI tools, but rather a great foundation for anyone who wants to take on a Generative AI course.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Become AI-Ready: Deep Learning Fundamentals

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Become AI-Ready: Deep Learning Fundamentals

Dozenten: LearnKartS

Bei enthalten

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3 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

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Empfohlene Erfahrung

8 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

3 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Anfänger

Empfohlene Erfahrung

8 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Build Neural Network Foundations to unlock AI,ML,and Generative AI career opportunities
Master Forward Pass & Backpropagationto debug, train, and optimizereal-world AI models
Decide ML vs Deep Learning Strategically to design scalable, production-ready AI systems
Understand RNNs, LSTMs & Sequence Models behind chatbots, forecasting, and GenAI apps

Kompetenzen, die Sie erwerben

Kategorie: Machine Learning
Kategorie: Recurrent Neural Networks (RNNs)
Kategorie: Model Optimization
Kategorie: Artificial Neural Networks
Kategorie: Deep Learning
Kategorie: Artificial Intelligence and Machine Learning (AI/ML)
Kategorie: Model Training
Kategorie: AI literacy

Werkzeuge, die Sie lernen werden

Kategorie: Generative AI
Kategorie: Tensorflow

Wichtige Details

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Februar 2026

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15 Aufgaben

Unterrichtet in Englisch

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In diesem Kurs gibt es 3 Module

Want to learn how AI systems work behind tools such as ChatGPT and develop a solid foundation for careers in AI & Generative AI?

Many professionals study AI theory but struggle to apply it to real-world systems. This course fills that gap by introducing you to how deep learning models are built, trained, and ultimately fail and get optimized in practice. Why This Course Works? 1) Real-World AI Focus – Learn where deep learning is used across GenAI, healthcare, and finance. 2) Industry Evolution Clarity – From Neural Networks → ImageNet → Generative AI shift. 3) Hands-On Understanding – Visual training using TensorFlow Playground and simulators. What You’ll Be Able To Do? -Build neural network foundations -Understand forward pass and backpropagation -Identify when to use ML vs Deep Learning -Understand RNN, LSTM, and sequence modeling This course is intended for software engineers, application developers, data analysts, professionals transitioning into AI & deep learning, as well as ML beginners who want to build job-ready AI skills. Build strong AI foundations, prepare for advanced deep learning and Generative AI roles. Enroll and start building future-ready AI skills today.

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.

Das ist alles enthalten

16 Videos5 Lektüren7 Aufgaben

16 VideosInsgesamt 62 Minuten

Why Deep Learning Is Powering Today’s AI Revolution1 Minute
What You’ll Be Able to Do After This Deep Learning Course2 Minuten
How Deep Learning Powers ChatGPT, Heathcare, and Finance Domain4 Minuten
Why Data Type Matters More Than Algorithm in AI4 Minuten
Learning Journey of Deep Learning till Gen AI3 Minuten
AI vs Machine Learning vs Deep Learning — Finally Explained Clearly4 Minuten
Types of Artifical Intelligence3 Minuten
History of Deep Learning4 Minuten
Imagenet Challenge - The Competition That Changed AI Forever5 Minuten
Transfer learning3 Minuten
Second Wave - The Moment Deep Learning Became Mainstream5 Minuten
When to Use Machine Learning vs Deep Learning6 Minuten
How AI Models Actually Learn From Data6 Minuten
How the Human Brain Inspired Neural Networks4 Minuten
How Activation Functions and Layers Power Neural Networks4 Minuten
Artificial Neural Networks5 Minuten

5 LektürenInsgesamt 45 Minuten

Real-World Deep Learning Applications - How a Hospital Reduced Cancer Diagnosis Errors Using Deep Learning5 Minuten
From Neural Networks to Generative AI: The Industry Shift10 Minuten
Why Deep Learning Failed in the 1990s and Returned Stronger10 Minuten
From ImageNet to Generative AI: Why Deep Learning Took Off10 Minuten
How Biological Neurons Inspired Artificial Neural Networks10 Minuten

7 AufgabenInsgesamt 112 Minuten

How AI, Machine Learning, and Deep Learning Actually Connect25 Minuten
Evolution of Deep Learning - The Breakthrough Moments That Made Deep Learning Powerful20 Minuten
How Machines Learn: From Brain Logic to Neural Networks15 Minuten
Deep Learning Foundations and Real-World Applications8 Minuten
Foundations of AI, Machine Learning, and Deep Learning16 Minuten
Evolution of Deep Learning - The Breakthrough Moments That Made Deep Learning Powerful16 Minuten
How Machines Learn: From Brain Logic to Neural Networks12 Minuten

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.

Das ist alles enthalten

14 Videos2 Lektüren4 Aufgaben

14 VideosInsgesamt 73 Minuten

Intro to Tensorflow Playground - Train Your First Neural Network Visually6 Minuten
Tensorflow playground Intro, Epochs7 Minuten
Tensorflow Playground - Watch a Neural Network Learn in Real Time4 Minuten
Tensorflow playground learning - Simple, medium complex cases6 Minuten
When Neural Networks Fail — And How to Fix Them4 Minuten
Parameters in Deep Learning : Tensorflow Playground1 Minute
Forward pass - What Happens When Data Enters a Neural Network5 Minuten
Learning - Neural networks7 Minuten
Back Propagation - How Neural Networks Learn From Mistakes6 Minuten
Backpropagation - Gradient descent7 Minuten
Backpropagation Step-by-Step With Real Numbers5 Minuten
Forward Pass + Backprop in Action using Network Simulator6 Minuten
Forward Pass Calculations + Loss Computation in Action using Network Simulator5 Minuten
Backpropagation + Weight Updates in Action using Network Simulator6 Minuten

2 LektürenInsgesamt 20 Minuten

Why Neural Networks Fail on Complex Patterns10 Minuten
How Data Flows Through Deep Neural Networks10 Minuten

4 AufgabenInsgesamt 72 Minuten

Train a Neural Network Visually Using TensorFlow Playground20 Minuten
Forward Pass and Backpropagation — The Core of Deep Learning Training20 Minuten
Train a Neural Network Visually Using TensorFlow Playground16 Minuten
Forward Pass and Backpropagation — The Core of Deep Learning Training16 Minuten

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.

Das ist alles enthalten

10 Videos4 Lektüren4 Aufgaben

10 VideosInsgesamt 42 Minuten

RNN - Why Deep Learning Needed Memory Models1 Minute
Sequence Modeling - How AI Understands Language, Speech, and Time Data5 Minuten
Language Modeling and Need for RNN6 Minuten
Recurrent Neural Networks (RNN) Concept and Network3 Minuten
Recurrent Neural Networks (RNN) Flow and Working Mechanism5 Minuten
Challenges in RNN5 Minuten
How LSTM Solves the Memory Problem in Deep Learning4 Minuten
Understanding LSTM Gate Operations and Information Flow5 Minuten
LSTM Gradient Flow and Backpropagation Through Time3 Minuten
Course Summary3 Minuten

4 LektürenInsgesamt 32 Minuten

Why Traditional Neural Networks Fail on Time-Based Data10 Minuten
How RNNs Remember Previous Information10 Minuten
Vanishing Gradient Problem Explained Without Math10 Minuten
Course Completion2 Minuten

4 AufgabenInsgesamt 45 Minuten

Why Deep Learning Needs Memory: Introduction to Sequence Modeling10 Minuten
Recurrent Neural Networks Explained — And Why They Struggle15 Minuten
Why Deep Learning Needs Memory: Introduction to Sequence Modeling8 Minuten
Recurrent Neural Networks Explained — And Why They Struggle12 Minuten

Dozenten

LearnKartS

160 Kurse201.415 Lernende

von

LearnKartS

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Häufig gestellte Fragen

Deep learning fundamentals describe the core concepts that underlie neural networks, how models are trained based on data usinglayers, weights, biases, and activation functions.These ideas underpin contemporary AI systems, such as image recognition,speech processing, and smart decision-making.

Yes. This course is intended for beginners and professionals new to AI. It breaks deep learning down using intuitive explanations and easy-to-understand examples, bridging the gap between theory and practice – no AI expertise required.

Machine learning is a large field dedicated to the study of learning from data, whereas deep learning is one of its subfields that employs multi-layer neural networks. Deep learning powers AI superpowers like vision, language understanding, and pattern recognition.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.