دوراتنا

A-level Mathematics for Year 12 - Course 1: Algebraic Methods, Graphs and Applied Mathematics Methods

Develop your thinking skills, fluency and confidence to aim for an A* in A-levelmaths and prepare for undergraduate STEM degrees.

• Course by
• التعلم الذاتي
• 12
• الإنجليزية

College Algebra

This College Algebra course will cover fundamental concepts of algebra required to interpret a variety of functions and equations.

This course is eligible for Audit and Verified Certificate only.

• Course by
• التعلم الذاتي
• 100
• الإنجليزية

Linear Algebra II: Matrices and Linear Transformations

This course provides an overview of bachelor-level linear algebra. You will review all the concepts and practice and refresh the skills related to matrices and linear transformations.

• Course by
• التعلم الذاتي
• 21
• الإنجليزية

Linear Algebra I: Vectors and Linear Equations

This course provides an overview of bachelor-level linear algebra. You will review all the concepts and practice and refresh the skills related to vectors and linear equations.

• Course by
• التعلم الذاتي
• 27
• الإنجليزية

Advanced Linear Algebra: Foundations to Frontiers

Learn advanced linear algebra for computing.

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• الإنجليزية

Linear Algebra - Foundations to Frontiers

Learn the mathematics behind linear algebra and link it to matrix software development.

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• الإنجليزية

Mathematics 1 Part 2: Integral calculus, algebra, and applications

The second in a series of two courses which help you to master mathematics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.

• Course by
• التعلم الذاتي
• الإنجليزية

Introduction to Machine Learning: Supervised Learning

In this course, you’ll be learning various supervised ML algorithms and prediction tasks applied to different data. You’ll learn when to use which model and why, and how to improve the model performances. We will cover models such as linear and logistic regression, KNN, Decision trees and ensembling methods such as Random Forest and Boosting, kernel methods such as SVM. Prior coding or scripting knowledge is required. We will be utilizing Python extensively throughout the course.

• Course by
• Self Paced
• 40 ساعات
• الإنجليزية

Advanced Statistics for Data Science

Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression. This specialization starts with Mathematical Statistics bootcamps, specifically concepts and methods used in biostatistics applications.

• Course by
• Self Paced
• الإنجليزية

Mechanics: Motion, Forces, Energy and Gravity, from Particles to Planets

Most of the phenomena in the world around you are, at the fundamental level, based on physics, and much of physics is based on mechanics. Mechanics begins by quantifying motion, and then explaining it in terms of forces, energy and momentum. This allows us to analyse the operation of many familiar phenomena around us, but also the mechanics of planets, stars and galaxies. This on-demand course is recommended for senior high school and beginning university students and anyone with a curiosity about basic physics.

• Course by
• Self Paced
• 29 ساعات
• الإنجليزية

Calculus through Data & Modeling: Differentiation Rules

Calculus through Data & Modeling: Differentiation Rules continues the study of differentiable calculus by developing new rules for finding derivatives without having to use the limit definition directly. These differentiation rules will enable the calculation of rates of change with relative ease the derivatives of polynomials, rational functions, algebraic functions, exponential and logarithmic functions, and trigonometric and inverse trigonometric functions.

• Course by
• Self Paced
• 8 ساعات
• الإنجليزية

Mathematics for Machine Learning

For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science.

• Course by
• Self Paced
• الإنجليزية

Linear Algebra for Data Science Using Python

This Specialization is for learners interested in exploring or pursuing careers in data science or understanding some data science for their current roles. This course will build upon your previous mathematical foundations and equip you with key applied tools for using and analyzing large data sets.

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• Self Paced
• الإنجليزية

Self-Driving Cars

Be at the forefront of the autonomous driving industry. With market researchers predicting a $42-billion market and more than 20 million self-driving cars on the road by 2025, the next big job boom is right around the corner. This Specialization gives you a comprehensive understanding of state-of-the-art engineering practices used in the self-driving car industry.

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• Self Paced
• الإنجليزية

Data Science Math Skills

Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time.

• Course by
• Self Paced
• 13 ساعات
• الإنجليزية

Linear Algebra Basics

Machine learning and data science are the most popular topics of research nowadays. They are applied in all the areas of engineering and sciences. Various machine learning tools provide a data-driven solution to various real-life problems. Basic knowledge of linear algebra is necessary to develop new algorithms for machine learning and data science. In this course, you will learn about the mathematical concepts related to linear algebra, which include vector spaces, subspaces, linear span, basis, and dimension.

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• 21 ساعات
• الإنجليزية

Mathematics for Machine Learning and Data Science

Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you’ll apply the math concepts you learn using Python programming in hands-on lab exercises.

• Course by
• Self Paced
• الإنجليزية

Introduction to Linear Models and Matrix Algebra

Learn to use R programming to apply linear models to analyze data in life sciences.

• Course by
• التعلم الذاتي
• 12
• الإنجليزية

Foundations of Quantum Mechanics

This course can also be taken for academic credit as ECEA 5610, part of CU Boulder’s Master of Science in Electrical Engineering degree. This course covers the fundamental concepts and topics of quantum mechanics which include basic concepts, 1D potential problems, time evolution of quantum states, and essential linear algebra. It provides undergraduate level foundational knowledge and build on them more advanced topics. At the end of this course learners will be able to: 1.

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• Self Paced
• 27 ساعات
• الإنجليزية

Digital Signal Processing 4: Applications

Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment. By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices. The goal, for students of this course, will be to learn the fundamentals of Digital Signal Processing from the ground up.

• Course by
• Self Paced
• 14 ساعات
• الإنجليزية

Physics 101 - Forces and Kinematics

This first course serves as an introduction to the physics of force and motion. Upon completion, learners will understand how mathematical laws and conservation principles describe the motions and interactions of objects around us. Learners will gain experience in solving physics problems with tools such as graphical analysis, algebra, vector analysis, and calculus. This first course covers 1D Kinematics, 2D Kinematics, and Newton's Laws. Each of the three modules contains reading links to a free textbook, complete video lectures, conceptual quizzes, and a set of homework problems.

• Course by
• Self Paced
• 30 ساعات
• الإنجليزية

Coaching Practices

In order for coaching to be most effective, it’s important that there is strong culture of coaching and accountability which you will learn how to incorporate into your one-on-one meetings in this course. We’ll discuss strategies in coaching great employees who are highly motivated, consistent performers, and poor performers. We’ll explore specific tools, such as a coaching agenda, you can employ immediately in your coaching conversations. You will learn how to use the "Coaching Algebra" technique in typical performance scenarios managers encounter.

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• Self Paced
• 19 ساعات
• الإنجليزية

Mathematics for Machine Learning: PCA

This intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique. We'll cover some basic statistics of data sets, such as mean values and variances, we'll compute distances and angles between vectors using inner products and derive orthogonal projections of data onto lower-dimensional subspaces.

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• Self Paced
• 21 ساعات
• الإنجليزية

Digital Signal Processing 1: Basic Concepts and Algorithms

Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment. By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices. In this series of four courses, you will learn the fundamentals of Digital Signal Processing from the ground up.

• Course by
• التعلم الذاتي
• 29 ساعات
• الإنجليزية

AI Workflow: Business Priorities and Data Ingestion

This is the first course of a six part specialization.  You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. This first course in the IBM AI Enterprise Workflow Certification specialization introduces you to the scope of the specialization and prerequisites.  Specifically, the courses in this specialization are meant for practicing data scientists who are knowledgeable about probability, statistics, linear algebra, and Python tooling for data science and ma

• Course by
• Self Paced
• 8 ساعات
• الإنجليزية