Machine Learning courses

1770 Courses

Pluralsight

Data Show and Tell: Exploring Trends in AI Research

Discover invaluable insights into AI research with our course, "Data Show and Tell: Exploring Trends in AI Research." Delve into a unique project that harnesses the power of natural language processing (NLP) to reveal prevailing trends in AI research papers. With AI research evolving rapidly, staying informed about its trends is essential fo.

Coursera

Applied Data Analytics

Begin your journey with the Applied Data Analytics Specialization, designed for both beginners and professionals. This program equips you with essential skills in Python, SQL, and Power BI to analyze, visualize, and extract actionable insights. Explore key concepts like data visualization, SQL queries, predictive modeling, and building dashb.

Coursera

Inside BFSI: Structure, Challenges, and Technology

Inside BFSI: Structure, Challenges, and Technology Course Description: Dive deep into the Banking, Financial Services, and Insurance (BFSI) sector with our comprehensive course. Discover the latest technological advancements and trends driving the industry. Gain invaluable insights into market segmentation, key players, and the regulatory landsca.

University of Michigan

AI for Energy and Biomedical Applications

“AI for Energy and Biomedical Applications” is a transformative exploration into the revolutionary AI technologies reshaping energy systems and healthcare solutions. In the energy domain, AI is a game-changer in the generation, distribution, and management of energy resources, optimizing renewable energy production, enhancing efficiency, a.

University of Michigan

AI for Autonomous Vehicles and Robotics

Immerse yourself in the transformative world where artificial intelligence meets autonomy in the course: AI for Autonomous Vehicles and Robotics. Offered by the University of Michigan, this course on Coursera provides a comprehensive journey into how machine learning algorithms are redefining autonomous systems. Explore the depths of supervis.

Coursera

Maximizing the Generative AI Value

Generative AI is transforming industries by automating creativity, optimizing processes, and fostering growth. This course, "Maximizing the Generative AI Value," empowers learners to leverage AI for innovative solutions and increased operational efficiency across various sectors. Studies show AI assists over 60% of daily tasks, enhancing outcom.

Coursera

Introduction to Security in the World of AI

Artificial Intelligence (AI) holds immense potential to revolutionize various sectors, yet it also brings forth unique security challenges. Our comprehensive course empowers leaders in security and data protection to adeptly manage AI within their enterprises. Acquire a robust framework that facilitates the proactive identification and miti.

University of Michigan

AI for Mechanical Engineers

AI for Mechanical Engineers is designed to empower mechanical engineering professionals with cutting-edge AI methodologies applicable in various domains. Offered by the University of Michigan on Coursera, this course series prepares you to integrate AI technologies effectively, enabling transformation in design processes, autonomous sys.

University of Michigan

AI for Design and Optimization

Artificial intelligence and machine learning are revolutionizing the way design processes are executed and optimizing strategies across various industries. The "AI for Design and Optimization" course equips you with the knowledge to leverage AI for enhancing your design and optimization capabilities. Master key skills to effectively utilize.

CourseHorse

Data Science and Machine Learning Bootcamp (Live Online)

Prepare for a prosperous career in some of the tech industry's most lucrative fields with our intensive 16-week Data Science and Machine Learning Bootcamp, hosted live online. This comprehensive program equips you with advanced skills in Python, SQL, Looker (Google Data Studio), Streamlit, and statistics, empowering you to excel as a pro.

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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!