Machine Learning courses

1332 Courses

Udemy

Complete Machine Learning & Data Science with Python| ML A-Z

Embark on a comprehensive journey into the world of Machine Learning and Data Science with Python. This course offers in-depth knowledge of tools like Numpy, Pandas, Matplotlib, Seaborn, and Scipy. Through this course, offered by Udemy, participants will gain practical insights into supervised and unsupervised machine learning techniques, along.

Udemy

Machine Learning: Master the Fundamentals

Discover the essentials of machine learning with Udemy's comprehensive course, "Machine Learning: Master the Fundamentals." This online course guides you through the intricacies of Python programming, Natural Language Processing (NLP), and Deep Learning techniques. Whether you're a beginner or looking to upgrade your skills, this course provi.

Udemy

Master in Data Science, Data Analytics and Data Analysis

Master in Data Science, Data Analytics, and Data Analysis | Udemy Boost your skills with the Master in Data Science, Data Analytics, and Data Analysis course available on Udemy. Dive into advanced topics such as Machine Learning, Artificial Intelligence, and Generative AI using popular programming languages like Python and R. Gain valuable.

Udemy

Linear Regression and Logistic Regression in Python

Discover the fundamentals of Linear Regression and Logistic Regression with this beginner-friendly course on Udemy. Designed for those with no prior experience in coding or mathematics, you'll learn to build predictive machine learning models efficiently and effectively. This course is part of Udemy's diverse offerings in Python, Machine Learni.

Udemy

Logistic Regression in Python

Logistic Regression in Python | Beginner's Tutorial | Udemy Take your first steps in mastering logistic regression with our Python tutorial tailored for beginners. This course will equip you with the foundational skills required for effective predictive modeling using Python. By the end, you'll be ready to tackle complex data analysis tasks with.

Udemy

ML for Business Managers: Build Regression model in R Studio

Master the fundamentals of Simple and Multiple Regression, crucial components of Machine Learning and Econometrics, by building a Regression model using R Studio. This course, offered by Udemy, provides a comprehensive introduction to Linear Regression, equipping Business Managers and aspiring data scientists with the skills necessary to leve.

Udemy

Machine Learning with Python : COMPLETE COURSE FOR BEGINNERS

Visit Udemy Embark on a comprehensive learning journey with the Machine Learning with Python: Complete Course for Beginners. This course, available on Udemy, is perfect for newcomers eager to explore the fascinating world of machine learning. In this course, you will: Understand the fundamentals of Python programming related to data science..

Udemy

2025 Machine Learning & Data Science for Beginners in Python

Welcome to the 2025 Machine Learning & Data Science for Beginners in Python course, brought to you by Udemy. Perfect for those eager to embark on their data science journey, this course covers a variety of essential projects. You will gain hands-on experience with techniques such as Linear Regression, Logistic Regression, Random Forest, Support.

Udemy

Machine Learning in GIS : Understand the Theory and Practice

Elevate your skills by exploring the synergies between Machine Learning and Geographic Information Systems (GIS) in this comprehensive course offered by Udemy. Delve into the principles and practical applications of Remote Sensing in QGIS and Google Earth Engine. This course is ideal for individuals eager to enhance their understanding of b.

Udemy

Decision Trees, Random Forests, Bagging & XGBoost: R Studio

Delve into the advanced world of Decision Trees and Ensembling techniques with our comprehensive course - Decision Trees, Random Forests, Bagging & XGBoost: R Studio, offered by Udemy. This course is specifically designed for those eager to enhance their understanding and application of R programming in machine learning. Throughout this course.

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Machine learning use cases

The use of machine learning has touched many areas in our lives. Let's look at the most striking examples of the use of computer intelligence:

Voice assistant Alisa. This system, without human help, will always find the answer to any question of interest, turn on music, answer the call and much more.

Selecting relevant advertising in browsers is not an easy process for a person, but it is quick for a computer. The system will analyze the viewing data and select what a particular user will like. The same system is used on various marketplaces - products that a person viewed or purchased are offered.

Chatbots in various dialogues. For example, many banks use bots to solve customer problems. It's convenient and fast.

Data security: Machine learning models can identify data security vulnerabilities before they become breaches. By analyzing past experiences, machine learning models can predict future high-risk actions so that risk can be mitigated proactively.

Finance: Banks, trading brokers and fintech firms use machine learning algorithms to automate trading and provide financial advisory services to investors. Bank of America uses chatbot Erica to automate customer support.

Healthcare: Machine learning is used to analyze massive medical data sets to speed up the discovery of treatments and cures, improve patient outcomes, and automate routine processes to prevent human errors. For example, IBM Watson uses data mining to provide doctors with data they can use to personalize patient care.

Fraud detection: AI is used in the finance and banking sector to autonomously analyze large numbers of transactions to identify fraudulent activities in real time. Technology services company Capgemini says fraud detection systems using machine learning and analytics reduce fraud investigation time by 70% and increase detection accuracy by 90% .

Retail: AI researchers and developers are using machine learning algorithms to develop AI recommendation engines that make relevant product suggestions based on shoppers' past choices, as well as historical, geographic and demographic data.

Facial recognition in the subway will help identify violators or criminals in a huge mass of people. Ordinary observers cannot cope with this task. But a fast-learning machine will do this job without any problems.

What do you need for machine learning (ML)?

For those interested in training, there are several requirements to be met in order to be successful in this field. So, there are the main points you need to know about the machine learning course. These requirements include:

Basic knowledge of programming languages such as Python, R, Java, JavaScript, etc.

Average knowledge of statistics and probability.

Basic knowledge of linear algebra in the ml course. In a linear regression model, a line is drawn through all the data points, and that line is used to calculate new values.

Understanding Calculus.

Knowledge of how to clean and structure raw data into the desired format to reduce the time required for decision making.

Machine learning courses from AI Eeducation are the best choice!