Deep Learning Courses and Certifications

Packt

Deep Learning - Recurrent Neural Networks with TensorFlow

Master recurrent neural networks for time series prediction and NLP tasks using TensorFlow. Implement advanced architectures like GRUs and LSTMs for stock forecasting, image classification, and text analysis.

• Coursera
• 5 hours 41 minutes
• On-Demand
• Paid Course

EDUCBA Microcredential

AI Deep Learning Projects with TensorFlow

Master practical deep learning by building neural networks, image captioning systems, and face mask detection apps using TensorFlow, with deployment on Streamlit and AWS.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 3 courses

EDUCBA Microcredential

Keras Deep Learning Projects with TensorFlow

Master hands-on deep learning with Keras and TensorFlow through real-world projects in chatbots, sentiment analysis, image classification, and face recognition for job-ready AI skills.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 4 courses

Coursera

Optimize Deep Learning: Tune PyTorch Models

Master PyTorch Lightning to implement custom callbacks, debug training issues, and optimize deep learning models for stable, production-ready performance.

• Coursera
• 3 hours 40 minutes
• On-Demand
• Paid Course

EDUCBA

Analyze and Build Deep Learning Models with TensorFlow

Master deep learning fundamentals and build practical TensorFlow models with hands-on implementation of neural networks, optimization techniques, and real-world applications.

• Coursera
• 4 hours 35 minutes
• On-Demand
• Paid Course

Code DeepSeek V3 From Scratch in Python - Full Course

Master the implementation of DeepSeek V3 from scratch with step-by-step Python coding instructions covering attention mechanisms, MLA, RoPE, KV Cache, MoE, and transformer blocks.

• freeCodeCamp
• 3 hours 47 minutes
• On-Demand
• Free Video

Stanford Seminar - Persistent and Unforgeable Watermarks for Deep Neural Networks

Explore persistent and unforgeable watermarking techniques for deep neural networks, focusing on IP protection, embedding methods, and resistance to attacks.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Online Course

Stanford Seminar - Mixture of Experts Paradigm and the Switch Transformer

Explore the Mixture of Experts paradigm and Switch Transformer, revolutionizing deep learning with sparsely-activated models for improved efficiency and performance in language processing tasks.

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

Stanford Seminar - Recent Progress in Verifying Neural Networks, Zico Kolter

Explore recent advancements in neural network verification, focusing on robustness and safety validation. Learn about innovative approaches that significantly speed up the verification process for medium-sized networks.

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

Intuitive Reasoning as Unsupervised Neural Generation

Explore intuitive reasoning in AI through neural generation, covering topics like common sense, language models, and multimodal information with researcher Yejin Choi.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Video

Instituto de Matemática Pura e Aplicada

Deep Learning e Aplicações

Explore os fundamentos do Deep Learning e suas aplicações revolucionárias em visão computacional, processamento de linguagem natural e análise de dados com Francisco Ganacim.

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

5 Minutes Engineering

Complete Deep Learning in 5 Hours Explained in Hindi

Master deep learning fundamentals through advanced architectures in Hindi - from neural networks and CNNs to RNNs, GANs, and transformers with practical Python implementation.

• YouTube
• 4 hours 41 minutes
• On-Demand
• Free Video

Deep Generative Models - Diffusion Models for Discrete Data - Lecture 18

Explore diffusion models for discrete data in this Stanford lecture, covering advanced techniques in deep generative modeling for AI applications.

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

Alexander Amini;  MIT

Deep Generative Modeling

1 review

Explore deep generative modeling, including autoencoders, variational autoencoders, and GANs. Learn about latent variable models, reparameterization tricks, and recent advances in generative AI techniques.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Yannic Kilcher

NeRF - Representing Scenes as Neural Radiance Fields for View Synthesis

Explore NeRF, a neural network-based approach for 3D scene representation and novel view synthesis, achieving photorealistic results from sparse input images through volumetric rendering.

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