HomeCoursesIntroduction to Deep Learning & Neural Networks

Updated 27 Aug

AI-powered learning

Save

Introduction to Deep Learning & Neural Networks

Name: Introduction to Deep Learning & Neural Networks
Price: 59 USD
Rating: 4.67 (75 reviews)
Author: AI Summer

Learn basic and intermediate deep learning concepts, including CNNs, RNNs, GANs, and transformers. Delve into fundamental architectures to enhance your machine learning model training skills.

4.7

52 lessons

4h 30min

Created by AI Summer

Introduction to Deep Learning & Neural Networks

What's included

52 lessons across 10 modules
8 quizzes with instant feedback
AI Tutor on every lesson

Join 3.1 million developers at

What You'll Learn

Understanding of the most popular Deep Learning models
A solid grasp on the mathematics and the intuition behind the algorithms
A good experience with Deep Learning Programming and Pytorch

Learning Roadmap

52 Lessons8 Quizzes1 Assessment11 Challenges

Learn Deep Learning

Get familiar with core deep learning concepts, models, hands-on exercises, and PyTorch tools.

About this Course

Why Learn Deep Learning?

Overview of the Course

Neural Networks

Walk through neural networks, including classifiers, optimization, backpropagation, and PyTorch basics.

Linear Classifiers

Optimization and Gradient Descent

Neural Networks

Backpropagation Algorithm

Build a Neural Network With Pytorch

Quiz Yourself on Neural Networks

Training Neural Networks

5 Lessons

Work your way through optimizing and training neural networks using key algorithms and techniques.

Convolutional Neural Networks

7 Lessons

Grasp the fundamentals of CNNs, including principles, applications, architectures, and improvements.

Recurrent Neural Networks

5 Lessons

Take a closer look at RNNs, LSTMs, and custom implementation in PyTorch for sequential data.

Autoencoders

5 Lessons

Investigate generative learning principles and explore autoencoders for data reconstruction and generation.

Generative Adversarial Networks

4 Lessons

Practice using GANs to generate realistic data and evaluate with discriminators for robustness.

Attention and Transformers

10 Lessons

Step through transformers, enhancing NLP tasks with self-attention, multi-head attention, and encoder-decoder mechanisms.

Graph Neural Networks

5 Lessons

Discover the logic behind Graph Neural Networks' applications, mathematics, and implementation details.

10.

Conclusion

2 Lessons

Examine deep learning advancements, essential tools, datasets, and resources for future learning.

Final Quiz

Assessment

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

About this course

WHY I WROTE THIS COURSE

This course is an accumulation of well-grounded knowledge and experience in deep learning. It provides you with the basic concepts you need in order to start working with and training various machine learning models. You will cover both basic and intermediate concepts including but not limited to: convolutional neural networks, recurrent neural networks, generative adversarial networks as well as transformers. After completing this course, you will have a comprehensive understanding of the fundamental architectural components of deep learning. Whether you’re a data and computer scientist, computer and big data engineer, solution architect, or software engineer, you will benefit from this course.

ABOUT THE AUTHOR

AI Summer

AI Summer provides educational content about Deep Learning and Artificial Intelligence. We are trying to collect and organize all Deep Learning related information from mathematics and models to programming and machine learning infrastructure.

Learn more about AI

Trusted by 3.1 million developers working at companies

These are high-quality courses. Trust me the price is worth it for the content quality. Educative came at the right time in my career. I'm understanding topics better than with any book or online video tutorial I've done. Truly made for developers. Thanks

Anthony Walker

@_webarchitect_

Just finished my first full #ML course: Machine learning for Software Engineers from Educative, Inc. ... Highly recommend!

Evan Dunbar

ML Engineer

You guys are the gold standard of crash-courses... Narrow enough that it doesn't need years of study or a full blown book to get the gist, but broad enough that an afternoon of Googling doesn't cut it.

Software Developer

Carlos Matias La Borde

I spend my days and nights on Educative. It is indispensable. It is such a unique and reader-friendly site

Souvik Kundu

Front-end Developer

Your courses are simply awesome, the depth they go into and the breadth of coverage is so good that I don't have to refer to 10 different websites looking for interview topics and content.

Vinay Krishnaiah

Software Developer

Course

Grokking the Machine Learning Interview

Your proven path to success in Machine Learning Interviews, developed by FAANG engineers. Unlock ML loops at top companies with a System Design approach.

15 h

intermediate

Course

Data Science Interview Handbook

The ultimate guide to data science interviews. Developed by FAANG engineers, it covers Python, algorithms, ML concepts, and interview questions. Get interview-ready in just a few hours.

9 h

intermediate

Course

Hands-on Machine Learning with Scikit-Learn

Gain insights into Scikit-Learn's datasets, feature engineering, linear/logistic regression, and unsupervised learning. Delve into k-means clustering and neural networks to enhance your machine learning expertise.

5 h

intermediate

Course

Grokking the Machine Learning System Design Interview

Gain insights into designing robust machine learning systems. Delve into key concepts, methodologies, and best practices to build efficient, scalable, and reliable ML solutions.

17 h

intermediate

Course

Grokking Computer Networking for Software Engineers

Learn networking essentials for software engineers: client-server models, Python sockets, CLI tools, key protocols, and hands-on distributed processing.

20 h

beginner

Course

Applied Machine Learning: Industry Case Study with TensorFlow

Gain insights into predicting retail sales with TensorFlow. Delve into data analysis, training models, and extracting insights using industry techniques. Explore efficient model evaluation with experts from top tech companies.

3 h

intermediate

Course

Building Advanced Deep Learning and NLP Projects

Gain insights into advanced deep learning and NLP by building 12 real-world projects using tools like TensorFlow and scikit-learn. Enhance your portfolio with industry-relevant skills.

5 h

intermediate

Course

A Beginner's Guide to Deep Learning

Gain insights into deep learning fundamentals, explore perceptron and advanced models, and discover practical coding in NumPy and Keras. Test your knowledge with quizzes and coding challenges.

20 h

beginner

Course

Grokking the Machine Learning Interview

intermediate

15 hour

Course

Data Science Interview Handbook

intermediate

9 hour

Course

Hands-on Machine Learning with Scikit-Learn