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Learn Machine Learning Algorithms online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
Johns Hopkins University
Data never arrive in the condition that you need them in order to do effective data analysis. Data need to be re-shaped, re-arranged, and re-formatted, so that they can be visualized or be inputted into a machine learning algorithm. This course addresses the problem of wrangling your data so that y…
IBM
A short hands-on project: Agentic AI, LLM, Machine Learning Algorithms.
This comprehensive AI Engineering roadmap will walk you through the essential skills and techniques every aspiring AI Engineer should master by 2025. From fundamental mathematics and key machine learning algorithms to deep learning, AI Engineering best practices, and large language models—you’ll ge…
Great Learning
Transfer learning is a very popular form of learning today. It aims to use a p[re-trained model to work on an entirely different dataset to see if meaningful results can be extracted when the machine learning algorithm is exposed to new data. Transfer learning is extremely popular because of the ef…
MIT OpenCourseWare
Linear algebra concepts are key for understanding and creating machine learning algorithms, especially as applied to deep learning and neural networks. This course reviews linear algebra with applications to probability and statistics and optimization–and above all a full explanation of deep learni…
Great Learning
In this course, IPL dataset is taken to analyze the metrics of different teams in IPL. Libraries such as pandas, matplotlib, and seaborn are used to perform exploratory data analysis on top of this IPL data. Finally, some machine learning algorithms are implemented to predict which team has a bette…
Delft University of Technology
Learn the fundamentals of machine learning to help you correctly apply various classification and regression machine learning algorithms to real-life problems using the Python toolbox scikit-learn.
Microsoft
This course covers the core algorithms and techniques used in AI and ML, including approaches that use pre-trained large-language models (LLMs). You will explore supervised, unsupervised, and reinforcement learning paradigms, as well as deep learning approaches, including how these operate in pre-t…
MITx
Become a data explorer – learn how to leverage data and basic machine learning algorithms to understand the world.
University of Michigan
In this course students will explore supervised machine learning techniques using the python scikit learn (sklearn) toolkit and real-world athletic data to understand both machine learning algorithms and how to predict athletic outcomes. Building on the previous courses in the specialization, stude…
Tsinghua University
The "Big Data Machine Learning" course is a basic theoretical course for senior undergraduates or graduate students in the information discipline. The purpose is to cultivate students to have an in-depth understanding of the theoretical basis of big data machine learning, a firm grasp of big data m…
IBM
Explore the exciting world of machine learning with this IBM course. Start by learning ML fundamentals before unlocking the power of Apache Spark to build and deploy ML models for data engineering applications. Dive into supervised and unsupervised learning techniques and discover the revolutionary…
IBM
This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you st…
A lot of machine learning algorithms can not deal with categorical data (like "favorite color" or "country code") directly. As a result, we have translate them into some sort of numerical value. The most common practice is to use something called One-Hot-Encoding, which is fine if you don't have ma…
University of Colorado Boulder
Products don't design and build themselves. In this course, students learn how to staff, plan and execute a project to build a product. We explore sensors, which produce tremendous volumes of data, and then storage devices and file systems for storing big data. Finally, we study machine learning an…
Microsoft
Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier.…
Universitat Politècnica de València
Aprende a valorizar y extraer conocimiento a partir de los datos, usando técnicas y herramientas de análisis de datos genéricas, y aprendizaje automático en particular.
University of California, Davis
Master probability fundamentals for machine learning. Explore probability rules, distributions, Bayes’ Theorem, and evaluation metrics like ROC and precision-recall curves. Build the skills to interpret uncertainty, model data, and make confident, data-driven decisions in ML applications.
University of Canterbury
Now that you know the basics of Bayesian inference, dive deeper to explore its richness and flexibility more fully. Let’s take a closer look at modeling latent variables, Bayesian model averaging, generalised linear models, and MCMC methods
This playlist provides an introduction to developing creative coding projects with machine learning. The theory and application of machine learning algorithms is demonstrated in JavaScript using the p5.js and ml5.js libraries. Learning Objectives: * Develop an intuition for and high level understan…
