Machine Learning Courses and Certifications

AI and Machine Learning Essentials

Explore AI and Machine Learning essentials, from foundational principles to real-world applications, ethical dilemmas, and future implications across business, technology, and society.

• Coursera
• 6 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Data Engineering & Pipeline Reliability for Machine Learning

Master data engineering skills using Python and pandas to clean, encode, validate datasets, build ML pipelines, manage schema changes, and optimize compute costs for production-ready ML infrastructure.

• Coursera
• 9 hours 3 minutes
• Self-Paced
• Paid Course

Packt

AWS Machine Learning Specialty Certification Guide

Master AWS Machine Learning Specialty (MLS-C01) exam prep by exploring SageMaker, data preparation, ML algorithms, and AI/ML services, with mock exams and hands-on AWS experience.

• Coursera
• 10 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Databricks Machine Learning Quickstart

Master rapid ML deployment on Databricks by tracking experiments with MLflow, leveraging AutoML for model selection, and deploying production-grade serving endpoints with performance monitoring.

• Coursera
• 2 hours 59 minutes
• Self-Paced
• Paid Course

Packt

Julia Programming for Data Science and Machine Learning

Master Julia v1.8 for data science and machine learning, covering type systems, metaprogramming, interoperability, visualization, and scientific computing with hands-on, real-world applications.

• Coursera
• 12 hours
• Self-Paced
• Paid Course

Packt Career Certificate

Machine Learning and Generative AI for Marketing

Master AI and ML techniques for marketing, from foundational analytics to generative AI, covering sentiment analysis, personalization, and ethical AI governance for data-driven strategies.

• Coursera
• Self-Paced
• Paid Course
• 3 courses

Coursera

Supervised Machine Learning

Master supervised ML skills—translate business problems into ML tasks, build linear models, SVMs, tree-based and ensemble models for classification, regression, and forecasting roles.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

Coursera

Training, Evaluating, and Monitoring Machine Learning Models

Master the full ML lifecycle—train models with mini-batch strategies, evaluate performance metrics, diagnose errors, and monitor production drift with A/B testing and retraining workflows.

• Coursera
• 9 hours 24 minutes
• Self-Paced
• Paid Course

Edureka

Getting Started with Automated Machine Learning (AutoML)

Master automated machine learning with H2O AutoML to build, evaluate, and deploy ML models efficiently without manual trial-and-error approaches.

• Coursera
• 10 hours 35 minutes
• Self-Paced
• Paid Course

Amazon Web Services;  Amazon

Developing Generative Artificial Intelligence Solutions

Explore the generative AI lifecycle, from defining use cases to deploying solutions. Learn to select, improve, and evaluate foundation models for effective AI application development.

• AWS Skill Builder
• 1 hour
• Self-Paced
• Free Certificate

Introduction to NLP Course (How To)

32-minute AI course: Ever wonder how Siri or Google Translate function? Jump into Natural Language Processing (NLP), the AI field that bridges the ...

• Treehouse
• 32 minutes
• Self-Paced
• Free Trial Available

Matrix Calculus for Machine Learning and Beyond

Explore advanced matrix calculus techniques for machine learning, optimization, and large-scale computing. Learn holistic matrix approaches, generalized derivatives, and reimagined differentiation formulas.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Mathematics of Big Data and Machine Learning

Explore the Dynamic Distributed Dimensional Data Model (D4M) to tackle Big Data challenges using graph theory, linear algebra, and databases. Apply this innovative approach to real-world problems in various fields.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Learning about LLM Webinar Series

Explore large language models, their applications, and Wolfram Language's unique tools for working with LLMs in this interactive series featuring expert discussions.

• Wolfram U
• 3 hours
• Self-Paced
• Free Online Course

Exploring AI Foundations with Wolfram Tools: Wolfram U Instructor-Led Course Series

Gain proficiency in machine learning, neural networks, and LLMs using Wolfram technologies. Build, train, and deploy models through hands-on projects and practical examples.

• Wolfram U
• 7 hours
• Self-Paced
• Free Certificate