Machine Learning Specialization Free Online Course applications are open for international applicants. Become an AI Specialist in Machine Learning. Learn the essentials of artificial intelligence and get useful machine learning abilities in this 3-course curriculum designed for beginners, taught by AI visionary Andrew Ng.

It offers a comprehensive introduction to contemporary machine learning, covering both supervised and unsupervised learning techniques (clustering, dimensionality reduction, recommender systems, multiple linear regression, logistic regression, and decision trees), as well as some of the best practices for AI and machine learning innovation utilized in Silicon Valley (model evaluation and tuning, data-centric performance improvement, and more.)

By the time this Specialization ends, you will have a firm grasp of fundamental ideas and acquired the useful skills necessary to swiftly and effectively apply machine learning to difficult real-world issues. The Machine Learning Specialization is the ideal place to start if you want to pursue a career in machine learning or break into the AI field.

Quick Details:

• Offered by: Stanford University and DeepLearning.AI
• Format: Online
• Deadline: Ongoing
• Duration: 2 months at 10 hours a week
• Gender: Any
• Type: Online Course
• Level: Beginner
• Eligible Nations: All

Benefits:

• Learn in-demand skills from professionals in academia and business.
• Learn a topic or tool through practical projects.
• Gain a thorough comprehension of the important ideas.
• Get a professional credential from Stanford University.

What Will You Learn?

You will learn:

• Create and train supervised models for prediction and binary classification tasks (linear, logistic regression) using NumPy and scikit-learn.
• Construct and train a neural network using TensorFlow for multi-class classification. Additionally, construct and apply decision trees and tree ensemble techniques.
• Utilize ML development best practices and unsupervised learning strategies, such as anomaly detection and clustering.
• Construct collaborative filtering recommender systems, content-based deep learning techniques, and deep reinforcement learning models.

Skills you’ll Gain:

• Decision Trees
• Recommender Systems
• Logistic Regression
• Artificial Neural Network
• Linear Regression

Eligibility Criteria:

Applicants must have the following:

• Anyone interested in obtaining this qualification might contact us.
• No upper age restrictions
• Students in any academic subject are welcome to apply for this position.
• Students need a stable internet connection because the course is offered online.
• Applicants must have the motivation to learn and apply new skills.

How to Apply?

Online enrollment is offered via Coursera. To begin registering, click the following link:

                             Apply Now

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For more details, kindly refer to Coursera’s website.