Machine Learning courses

1795 Courses

Text Analytics with Python

Learn the core techniques of text analytics and natural language processing (NLP) while discovering the cognitive science that makes it possible in this certificate Text Analytics with Python. On the practical side, you’ll learn how to actually do an analysis in Python: creating pipelines for text classification and text similarity using machine l.

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Tecnológico de Monterrey

Inteligencia Artificial y Robótica

La robótica y la inteligencia artificial son factores clave para el éxito y permanencia en el mercado de las diferentes industrias, la automatización industrial es una realidad. Según el Foro Económico Mundial, puestos laborales como Especialistas en Aprendizaje de Máquina (Machine Learning), Científico de Datos o Experto en Inteligencia Artifici.

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Tecnológico de Monterrey

Inteligencia Artificial aplicada a los negocios

Aprende a identificar los elementos de la inteligencia artificial que han impactado en los negocios. Conocerás las nuevas herramientas en Aprendizaje Máquina y cómo aplicarlas para la toma de decisiones exitosas para la empresa, considerando las buenas prácticas y los códigos de ética que vienen implícitos en el uso de las nuevas herramientas digi.

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Foundations of AI

71% of executives say they prefer to hire a candidate with AI skills (Forbes); the need to get up to speed with AI has never been more critical. This IBM Professional Certificate gives you a practical understanding of the core concepts and real-world application of AI, plus job-ready skills using gen AI in just 9 weeks. Whether you’re an experienc.

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IBM Applied AI Developer

92% of companies plan to increase their AI investments over the next three years (McKinsey). Talented AI developers are in high demand! This IBM Applied AI Developer Professional Certificate gives aspiring AI developers the job-ready skills to build AI-powered applications, virtual assistants, and chatbots employers are looking for in just 6 month.

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Generative AI Engineering

The gen AI market is projected to grow at an impressive 46% CAGR through 2030 (Statista). The demand for tech professionals skilled in generative AI engineering is skyrocketing! This Generative AI Engineering Professional Certificate gives aspiring generative AI engineers, AI developers, data scientists, machine learning engineers, and AI research.

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AWS Skill Builder

Automating with AI/ML for Small Business Owners

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey.This course provides small business owners with a high-level overview of generative artificial intelligence (AI). Learners.

AWS Skill Builder

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Artificial Intelligence & Machine Learning in Healthcare

In this two-course MicroMasters program, you will learn how Artificial Intelligence (AI) and Machine Learning (ML) can be used to improve healthcare. In the first self-paced course, you’ll build a solid foundation in AI and ML fundamentals, learning how these technologies can enhance both clinical and operational decision-making. You’ll also learn.

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Coursera

Machine Learning on Google Cloud

What is machine learning, and what kinds of problems can it solve? How can you build, train, and deploy machine learning models at scale without writing a single line of code? When should you use automated machine learning or custom training? This course teaches you how to build Vertex AI AutoML models without writing a single line of code; build B.

Coursera

Harvard University

Python for Data Science and Machine Learning

Have you thought about a career in data science and machine learning but didn’t know where to start? Demand for professionals in the machine learning (ML) and artificial intelligence (AI) space is growing exponentially, with no signs of slowing thanks to the ever changing data science landscape. In fact, as the availability of machine learning too.

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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!