Classification Courses and Certifications

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
• On-Demand
• Paid Course

Packt

Machine Learning: Random Forest with Python from Scratch©

Master Python and Random Forest algorithm for machine learning. Build predictive models, handle data, and optimize performance through hands-on projects and real-world applications.

• Coursera
• 10 hours 28 minutes
• On-Demand
• Paid Course

Board Infinity Microcredential

Java in Machine Learning

Master machine learning with Java using Weka, Smile, and Deeplearning4j. Build scalable ML applications from data preprocessing to deployment in enterprise environments.

• Coursera
• 12 weeks, 5 hours a week
• On-Demand
• Paid Course
• 3 courses

Edureka

Machine Learning with PySpark

Master distributed machine learning using PySpark MLlib to build scalable models, process large datasets, and implement advanced algorithms for classification, regression, and clustering in a big data environment.

• Coursera
• 13 hours 27 minutes
• On-Demand
• Paid Course

EDUCBA

PySpark: Apply & Evaluate Predictive ML Models

Master PySpark's MLlib to build, evaluate, and deploy scalable regression, classification, and clustering models using distributed computing for real-world data analytics.

• Coursera
• 5 hours 15 minutes
• On-Demand
• Paid Course

Packt

Intermediate Data Manipulation and Machine Learning

Explore AI fundamentals, regression analysis, model preparation, classification techniques, and advanced machine learning concepts through interactive labs and real-world applications.

• Coursera
• 13 hours 16 minutes
• On-Demand
• Paid Course

Supervised Learning

Master supervised learning algorithms like KNN, SVM, and Random Forest using Sklearn in Python, focusing on practical implementation and real-world problem-solving applications.

• edX
• 6 weeks, 5-7 hours a week
• On-Demand
• Free Online Course (Audit)

Packt

Advanced ML Algorithms & Unsupervised Learning

Master advanced machine learning techniques including Random Forest, SVM, PCA, K-Means clustering, and deep learning fundamentals to build more powerful predictive models and uncover patterns in unlabeled data.

• Coursera
• 8 hours 43 minutes
• On-Demand
• Paid Course

Packt

Exploratory Data Analysis & Core ML Algorithms

Master exploratory data analysis and core ML algorithms including linear regression, logistic regression, Naive Bayes, and decision trees through hands-on projects and real-world applications.

• Coursera
• 14 hours 5 minutes
• On-Demand
• 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
• On-Demand
• Paid Course

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
• On-Demand
• Paid Course

Coursera Microcredential

Statistical Inference & Predictive Modeling Foundations

Master statistical inference and predictive modeling through A/B testing, regression, neural networks, and ensemble methods to drive data-driven business decisions.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 8 courses

EDUCBA

Machine Learning with Python: Case Studies

Master machine learning through hands-on Python case studies covering regression, clustering, classification, and feature engineering with real-world datasets like salary prediction and credit risk.

• Coursera
• 8 hours 57 minutes
• On-Demand
• Paid Course

H2O.ai

DataPrep for H2O Driverless AI

Master data preparation techniques for machine learning using H2O's Driverless AI, covering tabular formats, time series analysis, and automated preprocessing for both supervised and unsupervised learning scenarios.

• Coursera
• 1 hour 9 minutes
• On-Demand
• Paid Course

Whizlabs

Fundamentals of Machine Learning

Master machine learning fundamentals with hands-on experience in supervised/unsupervised learning, data preparation, model optimization, and cloud deployment on AWS and Azure.

• Coursera
• 14 hours 59 minutes
• On-Demand
• Paid Course