Multilayer Perceptrons Courses and Certifications

Training Neural Networks: the Backpropagation Algorithm

Implement neural-network learning from scratch in R, from MSE loss and gradient descent through multilayer backpropagation and mini-batch SGD.

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

Career Certificate

Neural Networks from Scratch using C++

Build neural networks from scratch in C++, from neurons and MLPs through backpropagation and a reusable neural-network library.

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

EDUCBA

Deep Learning with R: Build & Predict Neural Networks

Prepare dataframes in R, apply descriptive statistics and Spearman correlation, plot trends, fit linear regressions, then build, run and test multilayer perceptron neural networks.

• Coursera
• 3 weeks, 4 hours a week
• Self-Paced
• Paid Course

Deep Learning Foundations & Azure Environments

Bridge custom PyTorch training with Azure ML infrastructure and MLflow tracking, from manual backpropagation to end-to-end cloud workflows.

• Coursera
• 7 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coding Train

Neural Networks - The Nature of Code

Dive into neural networks from perceptrons to backpropagation with hands-on coding examples, matrix math, and practical projects like doodle classification.

• YouTube
• 8 hours 48 minutes
• Self-Paced
• Free Video

Andrej Karpathy

Intro to Neural Networks and Backpropagation - Building Micrograd

Builds a minimal neural-network library from scratch to reveal backpropagation, gradient descent, and training under the hood.

• YouTube
• 2 hours 26 minutes
• Self-Paced
• Free Video

NPTEL;  IISc Bangalore

Neural Networks for Signal Processing - I

Introduces neural networks as optimization-driven directed graphs for signal-processing tasks, from perceptrons and multilayer models through kernels, SVMs, regularization, and PCA.

• Swayam
• 12 weeks
• Available until Oct 9, 2026
• Free Online Course

Google DeepMind: 03 Design And Train Neural Networks

Learn to design and train multilayer perceptrons, diagnose overfitting, and apply backpropagation and stochastic gradient descent through coding labs.

• Google Skills
• 4 hours
• Self-Paced
• Free Online Course

NPTEL-NOC IITM

Modern Computer Vision - Advanced Deep Learning Techniques for Image Processing

Explore advanced deep learning techniques for image processing, covering CNNs, RNNs, object detection, 3D reconstruction, and practical computer vision applications.

• YouTube
• 1 day 7 hours 34 minutes
• Self-Paced
• Free Video

Great Learning

Machine Learning Concepts - Comprehensive Tutorial Series

Discover essential machine learning algorithms, from linear regression to neural networks, with hands-on Python implementation and real-world applications.

• YouTube
• 1 day 14 hours 35 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

Neural Style Transfer

Dive into neural style transfer from basic theory to advanced implementations, covering optimization and feed-forward methods with hands-on PyTorch coding examples.

• YouTube
• 1 hour 33 minutes
• Self-Paced
• Free Video

Alexander Amini;  MIT

MIT Introduction to Deep Learning

An MIT lecture builds deep learning from perceptrons into neural networks, then trains them with loss functions, gradient descent, backpropagation, and regularization.

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

Alexander Amini;  MIT

Introduction to Deep Learning

Introduces deep learning foundations through perceptrons, neural networks, backpropagation, gradient descent, and regularization.

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

Data Science Courses

Deep Learning - STAT 940 - Fall 2023

Master neural networks from feedforward architectures to transformers, GANs, and diffusion models in this comprehensive university-level deep learning program.

• YouTube
• 23 hours 31 minutes
• Self-Paced
• Free Video

Valerio Velardo - The Sound of AI

Implementing and Training a Neural Network with PyTorch

Build and train a feed-forward neural network in PyTorch, using MNIST digit classification to explore datasets, data loaders, and training loops.

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