Machine Learning Courses and Certifications

Future of data and technology in football

Explore cutting-edge AI, machine learning, and advanced tracking technologies revolutionizing football analytics, scouting, and performance optimization.

• Coursera
• 21 hours 16 minutes
• Self-Paced
• Paid Course

Coursera

Architecting and Integrating Scalable AI Systems

Master the design of end-to-end AI architectures, integrating ML models into production using cloud platforms, APIs, and monitoring tools to build scalable, reliable systems.

• Coursera
• 10 hours 42 minutes
• Self-Paced
• Paid Course

Coursera

Predictive Models for Financial Risk

Master supervised machine learning for financial risk assessment through hands-on Python projects, data preparation, model validation, and transparent business communication.

• Coursera
• 1 hour 43 minutes
• Self-Paced
• Paid Course

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
• Self-Paced
• Paid Course

Coursera

Measure ML Impact & Business Value

Discover how to translate ML model performance into measurable business value through metric trees, experimental design, and ROI analysis for data-driven decision making.

• Coursera
• 4 hours 56 minutes
• Self-Paced
• 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
• Self-Paced
• Paid Course

Coursera Career Certificate

Systematic ML Optimization

Master systematic ML optimization techniques to transform experimental models into robust, production-ready systems that deliver sustained business value through reproducible workflows.

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

Coursera Career Certificate

ML Model Training & Validation

Master end-to-end ML model training, validation, and optimization for production environments through hands-on labs covering data preparation, algorithm comparison, and deployment.

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

EDUCBA

Analyze & Build a Churn Prediction Model in R

Master customer retention analytics by building and evaluating churn prediction models in R using logistic regression, data preprocessing, and performance metrics like ROC curves.

• Coursera
• 4 hours 45 minutes
• Self-Paced
• Paid Course

Packt

Building, Evaluating, and Operationalizing ML Models

Master the complete ML lifecycle from data exploration to deployment using Azure ML Studio, covering algorithm selection, model evaluation, and automated pipelines.

• Coursera
• 7 hours 49 minutes
• Self-Paced
• Paid Course

Coursera

Automate and Evaluate ML Pipeline Tests

Master ML pipeline testing with unit, integration, and smoke tests. Detect data drift, build automated regression suites with pytest, and deploy reliably using a reusable testing framework.

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

Coursera

Model Training & Evaluation

Master machine learning model training and evaluation through PyTorch practice, exploring mini-batch training, learning-rate schedulers, loss curve analysis, and class-imbalance techniques.

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

Board Infinity

Cloud Platforms for ML: AWS, Azure & GCP Deployment

Master ML deployment across AWS SageMaker, Azure ML Studio, and Vertex AI. Build serverless workflows, evaluate cost and scalability, and choose the right cloud platform for enterprise ML needs.

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

Coursera

Debug ML Code: Fix, Trace & Evaluate

Master debugging ML systems through structured workflows, unit testing, stack trace interpretation, and regression testing to build reliable machine learning codebases.

• Coursera
• 1 hour 39 minutes
• Self-Paced
• Paid Course

Coursera

Deconstruct AI: Complex ML Problems

Learn to break down complex ML systems into reusable components, create flowcharts and pseudocode, and design abstractions for fraud detection and feature store workflows in MLOps roles.

• Coursera
• 2 hours 45 minutes
• Self-Paced
• Paid Course