Is deep learning easy to learn?

Deep learning can be challenging due to its technical nature, but with structured resources, practical projects, and consistent effort, it becomes manageable even for beginners.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. 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.

Deep Learning Frameworks and Neural Networks Simplified

Deep Learning Frameworks and Neural Networks Simplified

本课程是 AI ML with Deep Learning and Supervised Models 专项课程的一部分

位教师：Simplilearn Instructor

包含在 Coursera Plus 中

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2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

5 小时完成

灵活的计划

自行安排学习进度

2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

5 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Master TensorFlow and Keras for model building and object detection
Apply RNNs and LSTM networks for sequential data tasks
Explore feedforward, convolutional, and recurrent neural networks
Build and deploy AI models to solve real-world challenges

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

作业

2 项作业

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

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

积累特定领域的专业知识

本课程是 AI ML with Deep Learning and Supervised Models 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有2个模块

By the end of this course, you will be able to: - Master TensorFlow and Keras: Learn TensorFlow’s architecture, features, and updates from 1.0 to 2.0, and use Keras for data handling and object detection. - Apply RNNs and LSTMs: Understand Recurrent Neural Networks, address the gradient problem, and implement Long Short-Term Memory (LSTM) networks for tasks like time series analysis and natural language processing. - Explore Neural Networks: Dive into feedforward, convolutional, and recurrent neural networks to understand their applications and functionality. - Develop Practical AI Solutions: Build and deploy advanced AI models for solving real-world problems in diverse industries. Guided by experts, you’ll gain the technical expertise and practical knowledge needed to excel in the fast-evolving field of deep learning.

This comprehensive Deep Learning program will equip you with advanced skills in TensorFlow, Keras, Recurrent Neural Networks (RNNs), and Neural Networks. You’ll learn to implement cutting-edge AI models and frameworks to tackle real-world challenges and drive impactful innovations. Guided by experts, you’ll gain the technical expertise and practical knowledge needed to excel in the fast-evolving field of deep learning.

涵盖的内容

11个视频2篇阅读材料1个作业

11个视频总计71分钟

Introduction to Different Frameworks1分钟
Introduction to Tensorflow0分钟
Tensors in Tensorflow2分钟
Tensorflow 1.0 vs 2.07分钟
Tensorflow Architechture5分钟
Introduction to Keras1分钟
Handling Dataframes using Keras Part 16分钟
Handling Dataframes using Keras Part 210分钟
Handling Dataframes using Keras Part 313分钟
Handling Dataframes using Keras Part 411分钟
Object Detection using Tensorflow10分钟

2篇阅读材料总计20分钟

Course Syllabus10分钟
Deep Learning Frameworks10分钟

1个作业总计50分钟

Assessment for Deep Learning Frameworks and Data Handling50分钟

Explore neural networks, RNNs, and LSTMs, and implement deep learning models using Keras.

涵盖的内容

15个视频2篇阅读材料1个作业

15个视频总计90分钟

What is Neural Network?1分钟
How Neural Network Works?3分钟
Types of Neural Network3分钟
Implemention using Keras5分钟
Use Case Implementation Part 14分钟
Use Case Implementation Part 25分钟
Use Case Implementation Part 310分钟
Use Case Implementation Part 44分钟
What is RNN?7分钟
Gradient Problem4分钟
LSTM8分钟
Implementation of LSTM6分钟
Use Case Implementation of LSTM Part 18分钟
Use Case Implementation of LSTM Part 27分钟
Use Case Implementation of LSTM Part 37分钟

2篇阅读材料总计20分钟

Neural Network for AI10分钟
RNN Simplified10分钟

1个作业总计70分钟

Assessment for Neural Networks and Sequential Models70分钟

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Simplilearn Instructor

Simplilearn

27 门课程25,500 名学生

提供方

Simplilearn

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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

TensorFlow and PyTorch are among the most popular frameworks for deep learning, offering robust libraries, community support, and flexibility for building and training neural networks.

Start with the basics of AI and machine learning, then progress to neural networks and frameworks like TensorFlow or PyTorch. Hands-on practice with projects and online courses can accelerate learning.

The three types of learning are supervised learning (using labeled data), unsupervised learning (working with unlabeled data), and reinforcement learning (training through rewards and penalties).

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.