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

Become AI-Ready: Deep Learning Fundamentals

位教师：LearnKartS

包含在中

了解更多

3个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

3个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

您将学到什么

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

您将获得的技能

要了解的详细信息

可分享的证书

添加到您的领英档案

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

该课程共有3个模块

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.

涵盖的内容

16个视频5篇阅读材料7个作业

16个视频总计62分钟

Why Deep Learning Is Powering Today’s AI Revolution 1分钟
What You’ll Be Able to Do After This Deep Learning Course 2分钟
How Deep Learning Powers ChatGPT, Heathcare, and Finance Domain 4分钟
Why Data Type Matters More Than Algorithm in AI 4分钟
Learning Journey of Deep Learning till Gen AI 3分钟
AI vs Machine Learning vs Deep Learning — Finally Explained Clearly 4分钟
Types of Artifical Intelligence 3分钟
History of Deep Learning 4分钟
Imagenet Challenge - The Competition That Changed AI Forever 5分钟
Transfer learning 3分钟
Second Wave - The Moment Deep Learning Became Mainstream 5分钟
When to Use Machine Learning vs Deep Learning 6分钟
How AI Models Actually Learn From Data 6分钟
How the Human Brain Inspired Neural Networks 4分钟
How Activation Functions and Layers Power Neural Networks 4分钟
Artificial Neural Networks 5分钟

5篇阅读材料总计45分钟

Real-World Deep Learning Applications - How a Hospital Reduced Cancer Diagnosis Errors Using Deep Learning 5分钟
From Neural Networks to Generative AI: The Industry Shift 10分钟
Why Deep Learning Failed in the 1990s and Returned Stronger 10分钟
From ImageNet to Generative AI: Why Deep Learning Took Off 10分钟
How Biological Neurons Inspired Artificial Neural Networks 10分钟

7个作业总计112分钟

How AI, Machine Learning, and Deep Learning Actually Connect 25分钟
Evolution of Deep Learning - The Breakthrough Moments That Made Deep Learning Powerful 20分钟
How Machines Learn: From Brain Logic to Neural Networks 15分钟
Deep Learning Foundations and Real-World Applications 8分钟
Foundations of AI, Machine Learning, and Deep Learning 16分钟
Evolution of Deep Learning - The Breakthrough Moments That Made Deep Learning Powerful 16分钟
How Machines Learn: From Brain Logic to Neural Networks 12分钟

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.

涵盖的内容

14个视频2篇阅读材料4个作业

14个视频总计73分钟

Intro to Tensorflow Playground - Train Your First Neural Network Visually 6分钟
Tensorflow playground Intro, Epochs 7分钟
Tensorflow Playground - Watch a Neural Network Learn in Real Time 4分钟
Tensorflow playground learning - Simple, medium complex cases 6分钟
When Neural Networks Fail — And How to Fix Them 4分钟
Parameters in Deep Learning : Tensorflow Playground 1分钟
Forward pass - What Happens When Data Enters a Neural Network 5分钟
Learning - Neural networks 7分钟
Back Propagation - How Neural Networks Learn From Mistakes 6分钟
Backpropagation - Gradient descent 7分钟
Backpropagation Step-by-Step With Real Numbers 5分钟
Forward Pass + Backprop in Action using Network Simulator 6分钟
Forward Pass Calculations + Loss Computation in Action using Network Simulator 5分钟
Backpropagation + Weight Updates in Action using Network Simulator 6分钟

2篇阅读材料总计20分钟

Why Neural Networks Fail on Complex Patterns 10分钟
How Data Flows Through Deep Neural Networks 10分钟

4个作业总计72分钟

Train a Neural Network Visually Using TensorFlow Playground 20分钟
Forward Pass and Backpropagation — The Core of Deep Learning Training 20分钟
Train a Neural Network Visually Using TensorFlow Playground 16分钟
Forward Pass and Backpropagation — The Core of Deep Learning Training 16分钟

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.

涵盖的内容

10个视频4篇阅读材料4个作业

10个视频总计42分钟

RNN - Why Deep Learning Needed Memory Models 1分钟
Sequence Modeling - How AI Understands Language, Speech, and Time Data 5分钟
Language Modeling and Need for RNN 6分钟
Recurrent Neural Networks (RNN) Concept and Network 3分钟
Recurrent Neural Networks (RNN) Flow and Working Mechanism 5分钟
Challenges in RNN 5分钟
How LSTM Solves the Memory Problem in Deep Learning 4分钟
Understanding LSTM Gate Operations and Information Flow 5分钟
LSTM Gradient Flow and Backpropagation Through Time 3分钟
Course Summary 3分钟

4篇阅读材料总计32分钟

Why Traditional Neural Networks Fail on Time-Based Data 10分钟
How RNNs Remember Previous Information 10分钟
Vanishing Gradient Problem Explained Without Math 10分钟
Course Completion 2分钟

4个作业总计45分钟

Why Deep Learning Needs Memory: Introduction to Sequence Modeling 10分钟
Recurrent Neural Networks Explained — And Why They Struggle 15分钟
Why Deep Learning Needs Memory: Introduction to Sequence Modeling 8分钟
Recurrent Neural Networks Explained — And Why They Struggle 12分钟

位教师

LearnKartS

134 门课程 176,528 名学生

提供方

LearnKartS

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无限制访问 10,000+ 世界一流的课程、实践项目和就业就绪证书课程 - 所有这些都包含在您的订阅中

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常见问题

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.

Become AI-Ready: Deep Learning Fundamentals

Become AI-Ready: Deep Learning Fundamentals

您将学到什么

您将获得的技能

要了解的详细信息

了解顶级公司的员工如何掌握热门技能

该课程共有3个模块

Module-1: AI to Deep Learning: Foundations Behind Modern Intelligent Systems

涵盖的内容

16个视频总计62分钟

5篇阅读材料总计45分钟

7个作业总计112分钟

Module-2: Inside Neural Networks: How Deep Learning Models Actually Learn

涵盖的内容

14个视频总计73分钟

2篇阅读材料总计20分钟

4个作业总计72分钟

Module-3: Sequence Intelligence: RNNs, LSTMs, and AI Memory Systems

涵盖的内容

10个视频总计42分钟

4篇阅读材料总计32分钟

4个作业总计45分钟

位教师

提供方

从 Machine Learning 浏览更多内容

Deep Learning, NLP, and AI Applications

AI & Deep Learning Concepts and Applications

NVIDIA: Fundamentals of Deep Learning

Fundamentals of Deep Learning

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

通过 Coursera Plus 开启新生涯

通过在线学位推动您的职业生涯

加入超过 3400 家选择 Coursera for Business 的全球公司

常见问题

更多问题

Become AI-Ready: Deep Learning Fundamentals

Become AI-Ready: Deep Learning Fundamentals

您将学到什么

您将获得的技能

要了解的详细信息

了解顶级公司的员工如何掌握热门技能

该课程共有3个模块

Module-1: AI to Deep Learning: Foundations Behind Modern Intelligent Systems

涵盖的内容

Module-2: Inside Neural Networks: How Deep Learning Models Actually Learn

涵盖的内容

Module-3: Sequence Intelligence: RNNs, LSTMs, and AI Memory Systems

涵盖的内容

位教师

提供方

从 Machine Learning 浏览更多内容

Deep Learning, NLP, and AI Applications

AI & Deep Learning Concepts and Applications

NVIDIA: Fundamentals of Deep Learning

Fundamentals of Deep Learning

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

通过 Coursera Plus 开启新生涯

通过在线学位推动您的职业生涯

加入超过 3400 家选择 Coursera for Business 的全球公司

常见问题

What are deep learning fundamentals?

Is this Coursera deep learning course suitable for beginners?

How is deep learning different from machine learning?

更多问题