Machine Learning Courses and Certifications

Amazon Web Services;  Amazon

AWS SimuLearn: Set Up an ML Environment

Learn to design and implement an ML environment on AWS using services like Lambda, S3, and SageMaker through interactive AI-powered simulations and hands-on practice in a live AWS Console.

• AWS Skill Builder
• 1 hour
• Self-Paced
• Paid Course

Amazon Web Services;  Amazon

AWS ML Engineer Associate Curriculum Overview

Explore machine learning fundamentals, AI evolution, and Amazon SageMaker in this advanced course. Learn to formulate ML problems, identify key algorithms, and develop responsible AI solutions for business goals.

• AWS Skill Builder
• 45 minutes
• Self-Paced
• Free Certificate

AI & Machine Learning Bootcamp (Live Online)

Learn the skills needed to excel by enrolling in the AI & Machine Learning Bootcamp at Fullstack Academy.

• CourseHorse
• 234 hours
• Self-Paced
• $14,495.00

Explore AWS ML stack, services, and processes. Learn how business problems transform into ML solutions, from data processing to model training and predictions.

• Independent
• 1 hour
• Self-Paced
• Free Online Course

Career Certificate

Machine Learning on Google Cloud

Comprehensive exploration of machine learning on Google Cloud, covering AutoML, BigQuery ML, custom training, feature engineering, and best practices for scalable ML implementation.

• Coursera
• 17 weeks, 6 hours a week
• Self-Paced
• Paid Course
• 5 courses

Career Certificate

Advanced Machine Learning on Google Cloud

Gain expertise in advanced ML topics using Google Cloud, covering optimization, deployment, and scaling of production models for structured data, images, time-series, and NLP, culminating in recommendation systems.

• Coursera
• 17 weeks, 5 hours a week
• Self-Paced
• Paid Course
• 5 courses

Career Certificate

Preparing for Google Cloud Certification: Machine Learning Engineer

Comprehensive program for aspiring ML engineers, covering Google Cloud's big data and ML services, TensorFlow, feature engineering, and MLOps. Includes hands-on labs and certification preparation.

• Coursera
• 30 weeks, 5 hours a week
• Self-Paced
• Paid Course
• 9 courses

Implement AI models with Microsoft Power Platform AI Builder

Implement AI models in Microsoft Power Platform, automating document processing, enhancing apps with ready-to-use models, recognizing text, and creating prediction models for streamlined workflows and improved user experiences.

• Microsoft Learn
• 3 hours 12 minutes
• Self-Paced
• Free Online Course

Career Certificate

Fundamentals of Google AI for Web Based Machine Learning

Explore AI and ML fundamentals, then dive into practical web-based applications using TensorFlow.js. Learn to create intelligent web apps with computer vision, natural language processing, and more.

• edX
• 11 weeks, 2-3 hours/week
• Self-Paced
• $598.00
• 2 courses

Career Certificate

Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs

Hands-on practice with BigQuery and Cloud Data Fusion for data analysis, warehousing, and machine learning on Google Cloud. Gain practical skills through virtual labs and earn a Skills Badge.

• Coursera
• 4 weeks, 5 hours a week
• Self-Paced
• Paid Course
• 4 courses

Machine Learning 101 with Scikit-learn and StatsModels

878 ratings at Udemy

New to machine learning? This is the place to start: Linear regression, Logistic regression & Cluster Analysis

• Udemy
• 5 hours 17 minutes
• Self-Paced
• Paid Course

Joint Learning Over Visual and Geometric Data

Explore joint learning approaches in visual and geometric domains to reduce supervision load, leveraging data correlations and self-supervision for improved performance and efficiency.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Efficiently Modeling Long Sequences with Structured State Spaces - Albert Gu

Explore structured state space models for efficient long sequence modeling across modalities, featuring S4's innovative approach to handling extended dependencies in various data types.

• YouTube
• 1 hour 7 minutes
• Self-Paced
• Free Video

Stanford Seminar - Computing with Physical Systems

Explores Physical Neural Networks and training complex physical systems for machine learning, showcasing experiments in mechanical, electronic, and photonic systems for tasks like handwritten-digit classification.

• YouTube
• 1 hour 9 minutes
• Self-Paced
• Free Video

Learning the Structure of EHR with Graph Convolutional Transformer - Edward Choi

Explore graph convolutional transformers for learning EHR structure, combining graph convolution and self-attention for supervised prediction tasks in healthcare analytics and representation learning.

• YouTube
• 1 hour 30 minutes
• Self-Paced
• Free Video