Automatic Differentiation Courses and Certifications

Engineering Design Optimization - Linear Constrained Optimization

Explore mathematical and algorithmic fundamentals of optimization for engineering systems design, covering linear and non-linear problems with emphasis on multidisciplinary applications.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Online Course

Matrix Calculus for Machine Learning and Beyond

Explore advanced matrix calculus techniques for machine learning, optimization, and large-scale computing. Learn holistic matrix approaches, generalized derivatives, and reimagined differentiation formulas.

• MIT OpenCourseWare
• On-Demand
• Free Online Course

Customising your models with TensorFlow 2

188 ratings at Coursera

Deepen TensorFlow skills to create custom deep learning models. Learn advanced APIs, complex architectures, and flexible data workflows. Develop a neural translation model in the capstone project.

• Coursera
• 1 day 3 hours 18 minutes
• On-Demand
• Free Online Course (Audit)

Deep Neural Networks with PyTorch

1682 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
• 1 day 7 hours 14 minutes
• On-Demand
• Free Online Course (Audit)

Yannic Kilcher

Efficient and Modular Implicit Differentiation - Machine Learning Research Paper Explained

Explores a unified framework for implicit differentiation in machine learning, enabling automatic differentiation of optimization problems without manual derivations or loop unrolling, with applications in meta-learning and hyperparameter optimization.

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

TensorFlow

Swift for TensorFlow - The Next-Generation Machine Learning Framework

Explore language-integrated automatic differentiation and optimized tooling in Swift for TensorFlow, enhancing machine learning productivity and innovation.

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

TensorFlow

Swift for TensorFlow - TF World '19

Explore Swift for TensorFlow, a cutting-edge ML platform integrating deep neural networks with AI algorithms and software development, enhancing research efficiency and speed.

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

AssemblyAI

JAX Crash Course - Accelerating Machine Learning Code

Accelerate machine learning with JAX: Learn NumPy-like operations on CPU, GPU, and TPU, automatic differentiation, and high-performance techniques for ML research in this comprehensive introduction.

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

MITCBMM

Computational Models of Cognition - Reverse-Engineering Common Sense in the Human Mind and Brain Pt 1

Explore cognitive modeling to reverse-engineer human common sense, examining AI progress, scientific context, and probabilistic programming techniques for capturing learning and constructing models.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Online Course

Association for Computing Machinery (ACM)

PyTorch - A Modern Library for Machine Learning with Adam Paszke

Explore PyTorch's capabilities in machine learning, from research to production. Learn about its innovative solutions for efficient inference and its versatility across various ML scenarios.

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

IEEE

Programming Languages for High-Assurance Vehicles

Explore secure programming for high-assurance vehicles using embedded domain-specific languages in Haskell, focusing on autopilot development, verification tools, and real-world applications.

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

Institute for Pure & Applied Mathematics (IPAM)

Methods for Scalable Probabilistic Inference - IPAM at UCLA

Explore scalable probabilistic inference methods for astrophysics, focusing on Gaussian Processes for time series analysis and open-source tools to accelerate Bayesian inference with large datasets.

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

GOTO Conferences

Inside Every Calculus Is A Little Algebra Waiting To Get Out

Explore algebraic approaches to automatic differentiation and integration in calculus, with Kotlin code examples. Learn how synthetic differential geometry simplifies complex mathematical concepts.

• YouTube
• 47 minutes
• On-Demand
• Conference Talk

GOTO Conferences

Teaching New Tricks to Old Programs Part 2

Explore advanced functional programming techniques for reinterpreting existing code, including hardware circuits, automatic differentiation, and interval analysis, using Haskell and GHC plugins.

• YouTube
• 31 minutes
• On-Demand
• Conference Talk

GOTO Conferences

Teaching New Tricks to Old Programs Part 1

Explore new interpretations for functional programs, including hardware circuits and automatic differentiation. Learn techniques for overloading lambda and organizing interpretations in Haskell.

• YouTube
• 30 minutes
• On-Demand
• Conference Talk