Research Methods Courses

Computational Thinking for K-12 Educators: Abstraction, Methods, and Lists

Explore abstraction, methods, lists, and recursion in programming. Develop teaching strategies for K-12 CS education, including culturally relevant pedagogy and low-frustration learning experiences.

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

Data Management for Clinical Research

5 ratings

Learn critical concepts and practical methods for planning, collecting, storing, and disseminating data in clinical research. Covers electronic data capture, regulatory compliance, and best practices for effective data management.

• Coursera
• 19 hours 20 minutes
• Self-Paced
• Paid Course

Quantitative Methods

7 ratings

Explore quantitative research methods in social sciences, focusing on scientific principles, research designs, measurement, sampling, and ethics. Gain skills to distinguish between solid research and flawed studies.

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

Econometrics: Methods and Applications

7 ratings

Learn to analyze economic data using regression models, handle endogeneity, binary choice, and time series data. Gain practical skills in forecasting and decision-making across various business fields.

• Coursera
• 2 days 18 hours 38 minutes
• Self-Paced
• Paid Course

Maximum Entropy Methods

10 ratings

In this tutorial, Simon DeDeo introduces MaxEnt through a series of examples, taking students from the basics of the subject up to its applications in science and engineering

• Complexity Explorer
• 1 hour
• Self-Paced
• Free Certificate

Advanced Deep Learning Methods for Healthcare

16 ratings at Coursera

Explore advanced deep learning techniques for healthcare, including attention models, graph neural networks, memory networks, and generative models. Apply these methods to real-world medical challenges through hands-on projects.

• Coursera
• 16 hours 28 minutes
• Self-Paced
• Paid Course

Deep Learning Methods for Healthcare

15 ratings at Coursera

Explore deep learning methods for healthcare applications, covering embedding, CNNs, RNNs, and autoencoders. Gain practical experience through labs, assignments, and a large project with potential for publication.

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

User Research and Design

472 ratings at Coursera

Learn and practice user research techniques, analyze and deliver findings, and generate design ideas through ideation methods for effective UI design.

• Coursera
• 9 hours 39 minutes
• Self-Paced
• Paid Course

Conflicts of Interest in Biomedical Research

Explore ethical concerns, safeguards, and policies related to conflicts of interest in biomedical research. Learn strategies for avoiding and managing conflicts through case studies and practical applications.

• Independent
• Self-Paced
• Free Certificate

Bioinformatics: Introduction and Methods 生物信息学: 导论与方法

286 ratings at Coursera

探索生物信息学的基本概念、计算方法及其在生物学中的应用,掌握序列比对、数据库搜索、马尔可夫模型等核心技能,为未来研究奠定基础。

• Coursera
• 1 day 1 hour 35 minutes
• Self-Paced
• Paid Course

Matrix Methods

249 ratings at Coursera

Explore fundamental matrix methods essential for machine learning and data analysis, including multiplication, linear equations, orthogonality, and SVD for dimensionality reduction and PCA.

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

Market Research and Consumer Behavior

4885 ratings at Coursera

Explore consumer decision-making and market research techniques to develop effective marketing strategies. Learn to analyze consumer behavior, conduct research, and interpret data for actionable insights.

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

Career Certificate

Plant Bioinformatic Methods

2148 ratings at Coursera

Explore plant biology through bioinformatics, covering genomics, transcriptomics, and protein interactions. Learn to use 33 plant-specific tools and apply them in a capstone project to hypothesize gene functions.

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

Bayesian Statistical Concepts and Methods

Master Bayesian methods for data analysis using posterior distributions, MCMC algorithms, and hierarchical models with R and Stan platform implementation.

• Coursera
• 5 hours 30 minutes
• Self-Paced
• Paid Course

Interview Research and Preparation

273 ratings at Coursera

Discover your strengths, passions, and career path. Learn to identify transferable skills and effectively communicate your value to potential employers. Improve English pronunciation and language learning efficiency.

• Coursera
• 1 day 2 hours 33 minutes
• Self-Paced
• Paid Course