Description
Mathematics for Computing by KodeKloud. This comprehensive course teaches the fundamentals and concepts of mathematics required for computer science, artificial intelligence, machine learning, and data science in a practical and tangible way. This course, developed by KodeKloud, is designed to demystify the mathematical concepts behind the digital world and modern software tools. In this comprehensive course, learners will learn the fundamentals of linear algebra and fully understand how to work with vectors, matrices, and tensors, which are the engines of graphics algorithms and search engines. In addition, this course explores the concepts of calculus, derivatives, and gradients, and shows how these mathematical tools enable machine learning and artificial intelligence algorithms to learn and optimize. In other parts of this course, participants will learn about probability distributions and Bayes’ theorem for statistical inference and accurate decision-making. It also provides a step-by-step, transparent look at how the back-propagation algorithm, which is used to train neural networks in areas such as language translation, works. This course is specifically designed for aspiring AI and machine learning engineers, data science beginners, and self-taught developers to turn abstract and complex mathematical formulas into practical, tangible tools that can be used in real-world projects.
What you will learn
- Learn the principles and foundations of linear algebra, including working with vectors, matrices, and tensors in computer science.
- Apply the concepts of calculus, derivatives, and gradients to understand machine learning and artificial intelligence algorithms.
- Analyze and interpret probability distributions and Bayes’ theorem for decision making and statistical inference.
- Deep understanding of how backpropagation works in training neural networks and artificial intelligence
This course is suitable for people who:
- Futuristic engineers and enthusiasts in the field of artificial intelligence and machine learning
- Beginners and newcomers to the world of data science
- Self-taught developers and programmers looking to strengthen their basic math knowledge
Course details for Mathematics for Computing by KodeKloud
- Publisher: LinkedIn
- Instructor: KodeKloud
- Education level: Intermediate
- Training duration: 2 hours and 27 minutes
Course topics
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 1080p
Download link
Rapidgator link
File(s) password: www.downloadly.ir
File size
816 MB