Machine Learning courses

1772 Courses

Coursera

Building AI Agents: Automation and NLP Foundations

Hey there, AI enthusiasts, tech trailblazers, and future-focused pros! Are you ready to explore the world of AI Agents and unleash the power of artificial intelligence? Buckle up for a deep dive into the cutting-edge tools and techniques transforming industries – and yes, your projects and workflows too! Why AI Agents? Did you know that by 2026, AI.

Coursera

AI ML with Deep Learning and Supervised Models

This comprehensive AI ML with Deep Learning and Supervised Models specialization equips you with the skills to excel in roles across AI, machine learning, and deep learning. Through in-depth modules, you'll master regression, classification, clustering, neural networks, and advanced AI frameworks to solve real-world challenges. By the end of this c.

Coursera

Preparing for Google Cloud Certification: Machine Learning Engineer

87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to advance your career and provides training to support your preparation for the industry-recognized Google Cloud Professional Machine Learning Engineer certification. Here's what you have to do: 1) Complete the Preparing for Goo.

Udemy

Generative AI for upskilling and learning initiatives

Be an expert at Generative AI in learning & upskilling & Learn how to use Generative AI in learning and development

Udemy

60 PDUs for your next PMP Renewal 2.0

Renew Your PMP Certification 2.0 : Get 60 PMP PDUs You Need To Satisfy PMI Requirements

edX

Detecting Anomalies with Machine Learning

Engineers are responsible for detecting abnormalities and ensuring reliability in the products they produce. Developments in artificial intelligence (AI) provide new tools for engineers to quicky identify anomalies and anticipate maintenance needs, preventing costly downtime and failures. Acquiring these skills will enable you to remain competitiv.

edX

Predicting Failures with Machine Learning

Engineers are tasked with minimizing downtime and enhancing operational reliability. Predictive maintenance has become a powerful way to predict equipment failures before they occur, leading to increased efficiency and cost savings. With operational efficiency being crucial to competitiveness, companies are seeking engineers with skills in applyin.

Udemy

Complete Generative AI for upskilling & learning initiatives

Master Generative AI in Personalized Learning and Upskilling and Learn Various types of Generative AI Models!

Udemy

AWS Certified AI Practitioner - AIF-C01

Prepare yourself for the AWS Certified AI Practitioner certification exam

Udemy

Custom ChatGPT Publishing & AI Bootcamp Masterclass

Learn Python, AI basics, ChatGPT customization, and build 150+ hands-on projects with zero prior experience.

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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!