Unsupervised Learning Courses and Certifications

Data Analytics and Machine Learning for Big Data

Master machine learning and AI techniques for big data systems using PySpark ML, PyTorch, and Azure tools to build end-to-end ML pipelines and integrate Generative AI workflows.

• Coursera
• 1 day 4 hours 27 minutes
• Self-Paced
• Paid Course

Maven Analytics

Complete Visual Guide to Machine Learning

Gain insights into machine learning fundamentals through visual examples and Excel-based models, covering classification, regression, forecasting, and unsupervised learning techniques - no coding required.

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

Saïd Business School

AI and Content Recommendation

Explore how AI-driven recommendation algorithms shape media, covering machine learning, filter bubbles, ethical risks, and Answer Engine Optimisation strategies for media professionals.

• Coursera
• 15 hours 15 minutes
• Self-Paced
• Paid Course

Packt Credential

Azure ML Bootcamp: Machine Learning on the Cloud

Master Azure Machine Learning from foundations to advanced MLOps deployment, building and operationalizing models with hands-on cloud experience and real-world applications.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Packt

Foundations of Machine Learning with Azure

Master machine learning fundamentals and Azure ML Studio through hands-on data preprocessing, model building, and deployment techniques for real-world business applications.

• Coursera
• 7 hours 29 minutes
• Self-Paced
• Paid Course

EDUCBA

Machine Learning with Python & Statistics

Master probability, sampling, distributions, and statistical testing to build machine learning models with Python and validate results through hypothesis testing and linear algebra.

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

EDUCBA

AI & Predictive Analytics with Python

Master AI and predictive analytics using Python, from ensemble methods and clustering to supervised learning, logic programming, and NLP with hands-on real-world applications.

• Coursera
• 11 hours 21 minutes
• Self-Paced
• Paid Course

Hewlett-Packard

AI Fundamentals: Core Concepts and Principles

Explore AI fundamentals from the 1956 Dartmouth Conference to modern machine learning, covering supervised, unsupervised, reinforcement learning, and the black box problem—no coding required.

• edX
• 9 hours
• Self-Paced
• Free Online Course (Audit)

Machine Learning for Healthcare Applications

Master machine learning techniques for healthcare analytics, building predictive models for clinical decision support, patient phenotyping, and temporal analysis with focus on interpretability.

• Coursera
• 7 hours 41 minutes
• Self-Paced
• Paid Course

Packt

Machine Learning for Absolute Beginners - Level 1

Discover foundational machine learning concepts, AI applications, and generative AI through hands-on examples, covering supervised learning, neural networks, and real-world challenges.

• Coursera
• 7 hours 21 minutes
• Self-Paced
• Paid Course

EDUCBA

Understand and Apply Artificial Intelligence Fundamentals

Explore AI fundamentals from core concepts to machine learning and reinforcement learning techniques for intelligent decision-making systems.

• Coursera
• 5 hours 58 minutes
• Self-Paced
• Paid Course

Coursera

Building and Optimizing AI Models

Master the full AI model lifecycle—design neural networks, apply transfer learning, optimize deep learning workflows, and benchmark performance using Python and TensorFlow.

• Coursera
• 7 hours 33 minutes
• Self-Paced
• Paid Course

Coursera

Optimize Vision Datasets: Augment and Analyze

Master vision dataset optimization through augmentation techniques and performance analysis using industry-standard validation methods and metrics interpretation.

• Coursera
• 2 hours 8 minutes
• Self-Paced
• Paid Course

EDUCBA

Analyze Fraud Using Data Analytics and R

Discover fraud detection using R and data analytics to identify patterns, evaluate techniques, and apply machine learning for fraud prevention and risk assessment.

• Coursera
• 5 hours 52 minutes
• Self-Paced
• Paid Course

Coursera

Detect AI Anomalies: Real-Time Outliers

Master statistical methods and unsupervised learning to build intelligent early warning systems that detect critical AI anomalies in real-time production environments.

• Coursera
• 2 hours 38 minutes
• Self-Paced
• Paid Course