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Deep Learning with Pytorch and Tensorflow2

Develop essential data science & ai skills with expert instruction and practical examples.

Online Course
Self-paced learning
Flexible Schedule
Learn at your pace
Expert Instructor
Industry professional
Certificate
Upon completion
What You'll Learn
Master the fundamentals of data science & ai
Apply best practices and industry standards
Build practical projects to demonstrate your skills
Understand advanced concepts and techniques

Skills you'll gain:

Professional SkillsBest PracticesIndustry Standards
Prerequisites & Target Audience

Skill Level

IntermediateSome prior knowledge recommended

Requirements

Basic understanding of data science & ai
Enthusiasm to learn
Access to necessary software/tools
Commitment to practice

Who This Course Is For

Professionals working in data science & ai
Students and career changers
Freelancers and consultants
Anyone looking to improve their skills
Course Information

About This Course

Welcome to the Deep Learning Fundamentals course on Udemy. Are you ready to unlock the power of neural networks and delve into the exciting world of artificial intelligence. Look no further.

This comprehensive course is designed to equip you with the essential knowledge and practical skills needed to become proficient in both Tensorflow and Pytorch based deep learning together. Deep learning has revolutionized the field of AI, enabling machines to learn from vast amounts of data and make accurate predictions, recognize patterns, and perform complex tasks. In this course, we will demystify the concepts behind deep learning and guide you through hands-on exercises to build and train your neural networks.

Here's an overview of what you'll learn:Introduction to Deep Learning:Understand the fundamentals of artificial neural networks. Explore the history and evolution of deep learning. Gain insights into real-world applications and their impact.

Neural Networks and Architectures:Study the structure and functioning of artificial neurons. Learn about various neural network architectures, including feedforward, convolutional, and recurrent networks. Explore activation functions, weight initialization, and regularization techniques.

Provider
Udemy
Estimated Duration
10-20 hours
Language
English
Category
Technology & Programming

Topics Covered

Data Science & AI

Course Details

Format
Online, Self-Paced
Access
Lifetime
Certificate
Upon Completion
Support
Q&A Forum
Course Details
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This course includes:

Lifetime access to course content
Access on mobile and desktop
Certificate of completion
Downloadable resources

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