Neural Networks Courses and Certifications

University of Helsinki;  MinnaLearn

Elements of AI

891 reviews

The elements of AI is a free online course for everyone interested in learning what AI is, what is possible (and not possible) with AI, and how it affects our lives – with no complicated math or programming required.

• Independent
• 6 weeks, 5-10 hours a week
• On-Demand
• Free Online Course

• Best of All Time

Stanford Seminar - Google's Multilingual Neural Machine Translation System

1 review

Exploring Google's Multilingual Neural Machine Translation system, its ability for zero-shot translation, and the potential existence of an interlingua in language processing.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

Stanford Seminar - Neural Networks on Chip Design from the User Perspective

We will briefly review our past effort on Deep learning Processing Unit (DPU) design on FPGA in Tsinghua and Deephi, and then talk about some features, i.e. interrupt and virtualization, we are trying to introduce into the accelerators from the user's pe…

• YouTube
• 58 minutes
• On-Demand
• Free Online Course

Optimizing for Interpretability in Deep Neural Networks - Mike Wu

Explore techniques for making deep neural networks more interpretable through regularization, focusing on medical applications in critical care and HIV treatment. Insights on balancing model performance with human-understandable decision processes.

• YouTube
• 51 minutes
• On-Demand
• Free Video

Self-Training - Weak Supervision Using Untrained Neural Nets for MR Reconstruction - Beliz Gunel

Exploring untrained neural networks for MR reconstruction, comparing self-training and weak supervision methods to improve performance with limited data while addressing slow inference times.

• YouTube
• 47 minutes
• On-Demand
• Free Video

Stanford Seminar - Concepts and Questions as Programs

Exploring human-like concept learning and question-asking through program induction and synthesis, with applications in visual recognition, active learning, and cognitive modeling.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Online Course

Neural Networks in R and the MNIST Data - Lecture 10.R.1

Explore neural networks using R and MNIST data, learning practical implementation of deep learning techniques for image recognition and statistical analysis.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Stanford Seminar 2022 - Transformer Circuits, Induction Heads, In-Context Learning

Explore reverse engineering of transformer language models, focusing on induction head circuits and their role in in-context learning. Gain insights into neural network interpretability and AI safety.

• YouTube
• 1 hour
• On-Demand
• Free Video

Democratizing Model Discovery with Neural Networks

Explore how neural networks revolutionize automated model discovery for soft materials, making it accessible to a diverse community and accelerating scientific innovation in various fields.

• YouTube
• 29 minutes
• On-Demand
• Free Video

Neural Networks Basics from Scratch

Master neural network fundamentals by building core AI components from scratch, including perceptrons, activation functions, and backpropagation - all without relying on high-level libraries.

• CodeSignal
• On-Demand
• Free Certificate

Advanced Neural Network Techniques

Master advanced neural network architectures including RNNs, Autoencoders, GANs, and Deep Reinforcement Learning through hands-on projects and real-world applications, from mathematical foundations to practical implementation.

• Coursera
• 10 hours 48 minutes
• On-Demand
• Free Online Course (Audit)

Introduction to Neural Networks

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
• 19 hours 54 minutes
• On-Demand
• Free Online Course (Audit)

Microcredential

Foundations of Neural Networks

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

• Coursera
• On-Demand
• Paid Course
• 3 courses

Mastering Neural Networks and Model Regularization

Dive deep into neural networks, from perceptrons to CNNs. Build models from scratch, master regularization techniques, and apply PyTorch for image and audio processing tasks.

• Coursera
• 16 hours 3 minutes
• On-Demand
• Free Online Course (Audit)

The Lottery Ticket Hypothesis - Michael Carbin

Explore the Lottery Ticket Hypothesis for efficient neural networks. Learn about pruning techniques, sparse architectures, and potential improvements in machine learning methods.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video