Numerical Methods Courses

API Authentication Methods with Swift

Master various API authentication methods in Swift, including API keys, session management with cookies, and JWT implementation for secure API interactions.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

API Authentication Methods with Dart

Master secure API communication in Dart using API keys, session cookies, and JWTs. Learn authentication flows including login, token refresh, and logout procedures for protected endpoints.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Ensemble Methods

Master ensemble methods by implementing Bagging, Random Forest, AdaBoost, and Stacking from scratch in C++ using mlpack for robust machine learning model aggregation.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

Theories and Methods of Learning and Teaching in Health Professions Education

Explore key learning theories and teaching methods to enhance health professions education, improve assessment strategies, and develop evidence-based lesson plans and feedback techniques.

• OpenLearning
• Self-Paced
• Paid Course

Commonly Used Biostatistical Methods for Analysing Longitudinal Data in Health Research

Use linear, logistic, Poisson and its variants regressions in the context of longitudinal studies in health, statistics and medical research.

• OpenLearning
• 24 hours
• Self-Paced
• Paid Course

Plant Breeding Methods

A blending of Conventional and Modern Techniques in Plant Breeding

• OpenLearning
• Self-Paced
• Paid Course

NUMERICAL DIFFERENTIATION & INTEGRATION

Master numerical differentiation and integration using Newton-Cotes formulas, combining methods for optimal accuracy while understanding trade-offs in selecting the best approach for any problem.

• OpenLearning
• Self-Paced
• Paid Course

Numerical Solution of Ordinary Differential Equations

Acquire fundamental principles of numerical methods to solve ordinary differential equations, analyzing mathematical and engineering problems where analytical methods fall short.

• OpenLearning
• Self-Paced
• Paid Course

Career Certificate

Statistical Methods for Computer Science

5 ratings at Coursera

Master advanced probability and statistical modeling techniques for data analysis, from fundamental concepts to computational methods, using R programming for real-world applications.

• Coursera
• 12 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 3 courses

Advanced Probability and Statistical Methods

Master advanced probability concepts through joint distributions, statistical testing, and Markov chains, building expertise in data analysis and statistical inference for real-world applications.

• Coursera
• 1 day 23 hours 46 minutes
• Self-Paced
• Paid Course

Advanced Methods in Machine Learning Applications

Master advanced machine learning techniques for complex problem-solving. Explore ensemble learning, regression analysis, unsupervised learning, and reinforcement learning. Gain practical skills to implement and optimize sophisticated models.

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

Bioinformatics Methods for Transcriptomics

Learn bioinformatics methods for analyzing RNA sequencing data, including gene expression, alternative splicing, and transcriptome reconstruction using popular tools like STAR, DESeq2, and Minimap2.

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

Neuroscience Methods

Master cutting-edge neuroscience methods, from neuroimaging and fNIRS to eye tracking and biometric systems. Gain practical skills in data collection, analysis, and research design for understanding cognitive and emotional processes.

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

Startup Valuation Methods

762 ratings at Coursera

Learn startup valuation methods, including discounted cashflow analysis, and explore different investor perspectives. Gain practical skills for evaluating investment opportunities and understanding various financing options for new ventures.

• Coursera
• 6 hours 48 minutes
• Self-Paced
• Paid Course

Practical Predictive Analytics: Models and Methods

323 ratings at Coursera

Explore statistical experiment design, analytics, and machine learning methods. Learn to design experiments, analyze results, and apply classification and unsupervised learning techniques to solve real-world problems.

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