Data Science

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Regression Models (Coursera) Coursera
Johns Hopkins University

Regression Models (Coursera)

Dive into Regression Models, a crucial course for aspiring data scientists on Coursera. Explore linear assumptions, learn how to relate outcomes to predictors effectively using regression analysis, and understand the principles of least squares and statistical inference. This course is perfect for those looking to deepen their understanding of essential statistical tools.

Sep 14th 2026
4 Weeks
Developing Data Products (Coursera) Coursera
Johns Hopkins University

Developing Data Products (Coursera)

Discover how to transform raw data into valuable insights with Coursera's 'Developing Data Products' course. Designed for those who want to create automated analytical tools or enhance data-driven models, this course equips you with essential skills in utilizing Shiny, R packages, and interactive graphics to build impactful data products.

Sep 14th 2026
4 Weeks
Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

Dive into 'Experimentation for Improvement' - a transformative course designed to equip you with the tools needed to optimize systems and processes efficiently. By focusing on planning effective experiments that test multiple variables simultaneously, this course aims to help you find the best solutions with minimal effort. Whether you're looking to innovate in your professional life or seeking to enhance community projects, this course will guide you through the process of optimization.

Sep 14th 2026
5-12 Weeks
Pattern Discovery in Data Mining (Coursera) Coursera
University of Illinois at Urbana-Champaign

Pattern Discovery in Data Mining (Coursera)

Dive into the fascinating world of data mining with our 'Pattern Discovery in Data Mining' course. This course will guide you through essential concepts, advanced methods, and real-world applications of pattern discovery. Master scalable pattern discovery techniques, evaluate patterns effectively, and explore sequential and sub-graph patterns to unlock hidden insights from massive transactional datasets.

Sep 14th 2026
4 Weeks
Introduction to Linear Models and Matrix Algebra (edX) EdX
HarvardX,Harvard University

Introduction to Linear Models and Matrix Algebra (edX)

Discover the essential principles of Linear Models and Matrix Algebra in this introductory data analysis course on edX. Perfect for those interested in life sciences, this program teaches you how to represent complex analyses with matrix algebra and perform statistical inference using R programming. Enhance your understanding of experimental design and high-dimensional data analysis.

Self Paced
Self-Paced
Text Retrieval and Search Engines (Coursera) Coursera
University of Illinois at Urbana-Champaign

Text Retrieval and Search Engines (Coursera)

Dive into the world of Text Retrieval and Search Engines with our expert-led course designed for those interested in mastering the retrieval and analysis of natural language text data. From web pages to social media posts, learn how to efficiently search, retrieve, and interpret human-generated content.

Sep 14th 2026
5-12 Weeks
Introduction to Bioconductor (edX) EdX
HarvardX,Harvard University

Introduction to Bioconductor (edX)

Dive into the world of genomics with 'Introduction to Bioconductor' on edX. This course unravels the complexities of genome-scale assays, offering insights into next-generation sequencing, microarrays, and how to effectively analyze and interpret genomic data using R and Bioconductor tools. Whether you're a biologist, bioinformatician, or just curious about genomics, this course provides a solid foundation.

Self Paced
Self-Paced
Advanced Bioconductor (edX) EdX
HarvardX,Harvard University

Advanced Bioconductor (edX)

Dive deep into the world of genomics with our Advanced Bioconductor course. Gain expertise in visualizing genome-scale data, building interactive interfaces for discovery, and mastering reproducible analysis through knitr and rmarkdown. Explore data architecture and analyze large consortium-generated datasets at scale.

Self Paced
Self-Paced