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Explore a wide range of free and certified Research methods online courses. Find the best Research methods training programs and enhance your skills today!
Construct optimal portfolios with Mean-Variance Analysis and CAPM in Excel, measure risk using VaR and CVaR, and model transaction costs from order books and bid-ask spreads.
Price options and interest rate products in Python: apply Fourier and FFT methods, calibrate Black-Merton-Scholes, Heston, Variance Gamma, Vasicek and CIR models to market data.
An eight-principle framework for ethical biomedical research in global settings, addressing trials, culturally adapted consent, ancillary care, and post-trial obligations.
Graduate course on using random constructions and probabilistic inequalities to prove the existence and properties of combinatorial objects.
Analyze protein purification schemes and structure determination, hemoglobin allostery and the Bohr effect, enzyme kinetics plots, membrane pumps and channels, and G protein signaling.
Master different data science methods such as time series analysis and machine learning that will enable you to conduct rigorous analysis, inform decision-making processes, and contribute to evidence
Builds the mathematical toolkit for quantitative finance through stochastic processes, optimization, statistical analysis, Monte Carlo simulation, and computational work in R.
Learn the mathematical foundations essential for financial engineering and quantitative finance: linear algebra, optimization, probability, stochastic processes, statistics, and applied computational
Apply numerical methods to chemical engineering problems: eigenvalues and SVD, Newton-Raphson solvers, ODE/DAE and PDE integration, constrained optimization, Monte Carlo, and stochastic chemical kinetics.
Solve engineering problems numerically: finite differences for wave and heat equations, conservation laws and shocks, sparse matrices, multigrid and Krylov solvers, constrained optimization and duality.
Examine how twentieth-century historians define their objects of study, build accounts from primary sources, and structure narrative and analysis, weighing each approach's strengths and limits.
Learn the experience design process: conduct design research with people, generate ideas through ideation techniques, synthesize data into personas and journey maps, and build low-fidelity prototypes.
Teach abstraction, method parameters, lists, and recursion in Snap: practice programming, diagnose common student bugs, and design culturally relevant assignments for computer science classrooms.
Plan, collect, store, and share clinical research data: structure variables, build REDCap forms and surveys, audit data quality, and de-identify records for sharing.
Separate sloppy science from solid research: study the scientific method, experimental and correlational designs, measurement and self-report instruments, sampling, and research integrity in the social sciences.
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