Quantitative Methods Courses

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

Bioinformatic Methods II

489 ratings at Coursera

Explore bioinformatics tools for analyzing large-scale biological data, including protein motifs, interactions, structures, gene expression, and cis-regulatory elements. Gain practical skills for extracting meaningful insights from genomic datasets.

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

Optimization Methods in Asset Management

48 ratings at Coursera

Explore optimization methods in asset management, covering Mean-Variance Analysis, CAPM, risk measurements, ETFs, and transaction costs modeling for practical portfolio construction and risk management.

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

Computational Methods in Pricing and Model Calibration

46 ratings at Coursera

Explore computational methods for pricing options and interest rate products, including numerical techniques, model calibration, and real-world applications using Python. Learn to analyze and implement various financial models.

• Coursera
• 1 day 26 minutes
• Self-Paced
• Paid Course

Numerical Methods Applied to Chemical Engineering

Explore advanced numerical methods for solving complex chemical engineering problems, including heat transfer, fluid mechanics, and molecular simulation. Gain practical skills in computational techniques.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Mathematical Methods for Engineers II

Explore advanced numerical methods for engineers, covering differential equations, network flows, and optimization. Gain practical skills in solving complex mathematical problems.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Seminar in Historical Methods

Explore diverse historical approaches, analyzing how historians structure narratives, use sources, and contribute to their fields. Gain insights into methodologies' strengths and limitations.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Quantitative Biology Workshop

Discover computational tools for biological research through hands-on Python, MATLAB, and R programming to analyze data and solve quantitative problems.

• MITx Online
• Self-Paced
• Free Online Course

Probabilistic Methods in Combinatorics

Master probabilistic methods in combinatorics and theoretical computer science, exploring random constructions, extremal set theory, and advanced mathematical concepts for proving existence of combinatorial objects.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course