Quantitative Methods Courses

Human-Computer Interaction IV: Evaluation, Agile Methods & Beyond

5 ratings at edX

Complete your understand of the design life cycle by learning to take interface ideas, prototype them quickly, and evaluate them with real users. Finally, tie principles and methods together and learn the next steps you could take in HCI.

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

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
• On-Demand
• Free Online Course

Biochemistry: Biomolecules, Methods, and Mechanisms

Dive into protein structures, enzyme kinetics, and cellular signaling mechanisms while developing essential scientific thinking and data analysis skills for biochemistry research.

• MITx Online
• On-Demand
• Free Online 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• Free Online Course

Microcredential

Statistics and Data Science (Methods Track)

Master advanced statistical methods and data science techniques for rigorous analysis, informed decision-making, and evidence-based practices across industries with MIT's comprehensive program.

• edX
• On-Demand
• $1,500.00
• 4 courses

Positive Psychology: Character, Grit and Research Methods

1233 ratings at Coursera

Explore research methods in Positive Psychology, focusing on character and grit. Learn to develop hypotheses, understand validity, and interpret empirical studies with leading experts.

• Coursera
• 23 hours 31 minutes
• On-Demand
• Paid Course

Ensemble Methods in Python

1 review

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Quantitative Risk Management in Python

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Quantitative Risk Management in R

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

• DataCamp
• 5 hours
• On-Demand
• Free Trial Available

Quantitative Analyst in R

Ensure portfolios are risk balanced, help find new trading opportunities, and evaluate asset prices using mathematical models.

• DataCamp
• 2 days 19 hours
• On-Demand
• Free Trial Available

Value-Based Methods

Apply deep learning architectures to reinforcement learning tasks. Train your own agent that navigates a virtual world from sensory data.

• Udacity
• 10 hours
• On-Demand
• Paid Course

Instructional Methods in Health Professions Education

544 ratings at Coursera

Enhance teaching skills for health professionals through interactive learning, covering theory, methods, and applied techniques for effective instruction across various stages and learners.

• Coursera
• 21 hours
• On-Demand
• Paid Course