Linear Algebra Courses and Certifications

Mathematical Foundations of Machine Learning

8308 ratings at Udemy

Essential Linear Algebra and Calculus Hands-On in NumPy, TensorFlow, and PyTorch

• Udemy
• 16 hours 26 minutes
• Self-Paced
• Paid Course

Mathematics for Machine Learning: PCA

3 ratings

Explore mathematical foundations of Principal Component Analysis (PCA) for dimensionality reduction. Learn statistics, inner products, orthogonal projections, and derive PCA from a geometric perspective.

• Coursera
• 20 hours 39 minutes
• Self-Paced
• Paid Course

Introduction to Self-Driving Cars

1 rating

Explore hardware, software, safety, and control systems for autonomous vehicles. Develop Python code to navigate a simulated self-driving car on a racetrack using CARLA.

• Coursera
• 1 day 11 hours 10 minutes
• Self-Paced
• Paid Course

Career Certificate

Self-Driving Cars

Master autonomous vehicle technology through hands-on projects using CARLA simulator. Gain comprehensive understanding of state-of-the-art engineering practices and build your own self-driving software stack.

• Coursera
• 12 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 4 courses

Career Certificate

Essential Mathematics for Computer Science

Master discrete mathematics, logic, algebra, calculus, and algorithmic reasoning to build the rigorous mathematical foundation essential for computing, data science, and software engineering.

• Coursera
• 8 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 5 courses

Master MATLAB through Guided Problem Solving

4322 ratings at Udemy

Become an expert in MATLAB Programming and Scientific Computing. Advance your career in Engineering Physics Biology etc

• Udemy
• 1 day 13 hours 58 minutes
• Self-Paced
• Paid Course

Mathematics-Basics to Advanced for Data Science And GenAI

3787 ratings at Udemy

Build Strong math foundation with linear algebra,stats,probability,differential calculus for mastering data science

• Udemy
• 22 hours 56 minutes
• Self-Paced
• Paid Course

Career Certificate

Mathematics for Machine Learning

1 rating

Gain essential mathematical foundations for machine learning, covering linear algebra, multivariate calculus, and dimensionality reduction with PCA. Build intuitive understanding and practical skills for advanced ML and data science.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Foundations of Quantum Mechanics

Explore wave-particle duality, Schrödinger equation, and quantum measurements. Master mathematical tools for quantum mechanics and gain foundational knowledge for advanced topics.

• Coursera
• 1 day 2 hours 40 minutes
• Self-Paced
• Paid Course

Career Certificate

Expressway to Data Science: Essential Math

Concise overview of foundational mathematics critical for Data Science careers, covering algebra, calculus, linear algebra, and numerical analysis. Prepares learners for advanced studies and applications in the field.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Modern Regression Analysis in R

Foundational statistical modeling tools for data science, covering linear models, parameter estimation, diagnostics, and ethical implications. Practical skills in R for regression analysis and model selection.

• Coursera
• 1 day 21 hours 27 minutes
• Self-Paced
• Paid Course

Integral Calculus and Numerical Analysis for Data Science

Intuitive approach to integral calculus and numerical analysis, covering integration, root-finding, matrix decomposition, and partial derivatives for data science applications.

• Coursera
• 3 hours 32 minutes
• Self-Paced
• Paid Course

Introduction to Machine Learning: Unsupervised Learning

Explore unsupervised machine learning techniques for dimensionality reduction, clustering, and latent feature discovery. Apply these methods to real-world scenarios like recommender systems using Python.

• Coursera
• 14 hours 54 minutes
• Self-Paced
• Paid Course

BiteSize Python: NumPy and Pandas

Master data manipulation and analysis with NumPy and Pandas libraries, exploring multidimensional arrays, Series, DataFrames, and essential statistical operations for efficient handling of large datasets.

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

Introduction to Neural Computation

1 rating

This course introduces quantitative approaches to understanding brain and cognitive functions.

• MIT OpenCourseWare
• 25 hours
• Self-Paced
• Free Video