HomeCoursesIntroduction to Deep Learning & Neural Networks

Intermediate

4h 30min

Introduction to Deep Learning & Neural Networks

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

Join 2.7 million developers at

Overview

Content

Reviews

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.

This course is an accumulation of well-grounded knowledge and experience in deep learning. It provides you with the basic concep...Show More

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

Understanding of the most popular Deep Learning models

TAKEAWAY SKILLS

Machine learning paradigms

Deep learning basics

PyTorch basics

Content

52 Lessons8 Quizzes1 Assessment11 Challenges

Learn Deep Learning

3 Lessons

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

6 Lessons

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.

Optimization

Popular Optimization Algorithms

Activation Functions

Training in Pytorch

Quiz Yourself on Training Neural Networks

Convolutional Neural Networks

7 Lessons

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

The Principles of the Convolution

Convolution in Practice

Build a Convolutional Network

Batch Normalization and Dropout

Skip Connections

CNN Architectures

Quiz Yourself on CNNs

Recurrent Neural Networks

5 Lessons

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

A Simple RNN Cell

LSTM: Long Short Term Memory Cells

Writing a Custom LSTM Cell in Pytorch

Connect LSTM Cells Across Time and Space

Quiz Yourself on RNNs

Autoencoders

5 Lessons

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

Generative Learning

Basics of Autoencoders

Variational Autoencoder: Theory

Variational Autoencoder: Practice

Quiz Yourself on Autoencoders

Generative Adversarial Networks

4 Lessons

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

Generator and Discriminator

Generative Adversarial Networks in Detail

Develop a GAN with Pytorch

Quiz Yourself on GANs

Attention and Transformers

10 Lessons

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

Sequence to Sequence Models

Attention

Key Concepts of Transformers

Self-Attention

Multi-Head Self-Attention

Transformers Building Blocks

The Transformer's Encoder

The Transformer's Decoder

Build a Transformer Encoder

Quiz Yourself on Transformers

Graph Neural Networks

5 Lessons

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

Basics of Graphs

Mathematics for Graphs

Graph Convolutional Networks

Implementation of a GCN

Quiz Yourself on GNNs

10.

Conclusion

2 Lessons

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

Where to go from here?

Appendix

Final Quiz

Assessment

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

AI Summer

Developed by MAANG Engineers

Every Educative resource is designed by our team of ex-MAANG software engineers and PhD computer science educators — subject matter experts who’ve shipped production code at scale and taught the theory behind it. The goal is to get you hands-on with the skills you need to stay ahead in today's constantly evolving tech landscape. No videos, no fluff — just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

Trusted by 2.7 million developers working at companies

"These are high-quality courses. Trust me. I own around 10 and the price is worth it for the content quality. EducativeInc 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

Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Personalized Interview Prep

Skip the LeetCode grind with a custom roadmap that adapts to your goals. Hands-on practice for Coding Interviews, System Design, and more.

Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

AI Prompt

Build prompt engineering skills. Practice implementing AI-informed solutions.

Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

Explain with AI

Select any text within any Educative course, and get an instant explanation — without ever leaving your browser.

AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

Course

Machine Learning System Design

Gain insights into ML system design, state-of-the-art techniques, and best practices for scalable production. Learn from top researchers and stand out in your next ML interview.

1 h 30 m

intermediate

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 Computer Networking for Software Engineers

Discover networking essentials for software engineers, delving into client-server architectures, Python socket programming, command-line tools, and key network protocols. Gain hands-on experience in 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

Machine Learning System Design

intermediate

1 hour 30 min

Course

Grokking the Machine Learning Interview

intermediate

15 hour

Course

Data Science Interview Handbook