Feedforward Neural Networks Courses and Certifications

Data Science Courses

Deep Learning: Feedforward Neural Networks and Backpropagation - Lecture 2

Dive into fundamental concepts of deep learning, exploring perceptrons, feedforward neural networks, and mastering backpropagation techniques for neural network training.

• YouTube
• 1 hour 16 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Feedforward Neural Networks and Backpropagation - Part 2

Dive into the second part of feedforward neural networks and backpropagation concepts, continuing the exploration of these fundamental neural network mechanisms.

• YouTube
• 22 minutes
• Self-Paced
• Free Video

UofU Data Science

Neural Networks Foundations - Feedforward Neural Networks

Master the fundamentals of feedforward neural networks, exploring their architecture, functionality, and implementation principles for building effective machine learning models.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

Deconstructing the Transformer Architecture

Master the Transformer architecture by building Multi-Head Attention, feed-forward networks, positional encodings, and complete encoder/decoder layers as reusable PyTorch modules from scratch.

• CodeSignal
• 4 hours
• Self-Paced
• Free Certificate

Introduction to Neural Networks and PyTorch

1901 ratings at Coursera

Learn to build and train deep neural networks using PyTorch, covering tensors, linear regression, logistic regression, CNNs, and transfer learning for practical AI applications.

• Coursera
• 18 hours 4 minutes
• Self-Paced
• Paid Course

Introduction to Neural Networks and Deep Learning with Python

Explore neural networks and deep learning with Python, covering optimization, regularization, transfer learning, and autoencoders to build, train, and evaluate models for real-world AI applications.

• edX
• 32 hours
• Self-Paced
• Free Online Course (Audit)

Credential

Foundations of Neural Networks

24 ratings at Coursera

Master advanced neural network concepts, from foundational theory to practical implementation in Python, while exploring ethical considerations in AI system development.

• Coursera
• 12 weeks, 4 hours/week
• Self-Paced
• Paid Course
• 3 courses

Introduction to Neural Networks

10 ratings at Coursera

Master foundational concepts of neural networks, from basic mathematics to advanced architectures like CNNs. Build practical skills in deep learning, optimization techniques, and model training through hands-on experience.

• Coursera
• 18 hours 20 minutes
• Self-Paced
• Paid Course

A deep understanding of deep learning (with Python intro)

6254 ratings at Udemy

Master deep learning in PyTorch using an experimental scientific approach, with lots of examples and practice problems.

• Udemy
• 2 days 9 hours 19 minutes
• Self-Paced
• Paid Course

Deep Learning for Natural Language Processing

Master neural networks for NLP, from feedforward and recurrent networks to transformers, transfer learning, and large language models, with practical implementation skills.

• Coursera
• 21 hours 3 minutes
• Self-Paced
• Paid Course

Machine Learning with Neural Networks

Explore neural network fundamentals, backpropagation, regularization, and Bayesian methods for machine learning with hands-on TensorFlow implementation.

• Coursera
• 1 day 12 hours 52 minutes
• Self-Paced
• Paid Course

Applied Natural Language Processing in Engineering Part 2

Master advanced NLP techniques including RNNs, transformers, sentiment analysis, and neural machine translation through hands-on implementation with PyTorch and Hugging Face frameworks.

• Coursera
• 1 day 9 hours 37 minutes
• Self-Paced
• Paid Course

Packt

Foundations of Deep Learning and Neural Networks

Master deep learning fundamentals, from neural network basics to advanced CNNs. Explore backpropagation, regularization techniques, and practical applications using TensorFlow and Keras. Ideal for tech professionals and students.

• Coursera
• 14 hours 19 minutes
• Self-Paced
• Paid Course

Coursera

Start Neural Networks Advanced Model Architectures

Master advanced neural network architectures with hands-on Keras/PyTorch implementation, regularization techniques, and systematic evaluation for real-world applications.

• Coursera
• 2 hours 16 minutes
• Self-Paced
• Paid Course

NPTEL;  IIT Ropar

Deep Learning

In this course, we will learn about the building blocks used in these Deep Learning based solutions. Specifically, we will learn about feedforward neural networks, convolutional neural networks, recurrent neural networks and attention mechanisms.

• YouTube
• 1 day 3 hours
• Self-Paced
• Free Video