Statistics & Data Analysis

Sort options

Data Analysis with Spreadsheets and SQL (Coursera)

Apr 1st 2024
Data Analysis with Spreadsheets and SQL (Coursera)
Course Auditing
Categories
Effort
Languages
This course introduces you to how to use spreadsheets and SQL queries to analyze and extract data. You will learn how to practically apply the OSEMN data analysis framework and spreadsheet functions to clean data, calculate summary statistics, evaluate correlations, and more. You’ll also dive into common data visualization [...]

Linear Regression (Coursera)

This course is best suited for individuals who have a technical background in mathematics/statistics/computer science/engineering pursuing a career change to jobs or industries that are data-driven such as finance, retain, tech, healthcare, government and many more. The opportunity is endless.

Data Ecosystem (Coursera)

The Data Ecosystem course will give you a foundational understanding of the entire data ecosystem, including data management. Specifically, this course shows how a business intelligence analyst would organize, access, and use data. You will learn about a variety of data sources along with the use and purpose of [...]

Introduction to Business Analytics (Coursera)

The Introduction to Business Analytics teaches you the foundational skills in Tableau and business analytics. You will be introduced to essential concepts like analytics and insights and the foundational steps of the business analysis process. You’ll learn about the different types of analytics that businesses use, and you’ll be [...]

Business Analysis Process (Coursera)

The Business Analysis Process course will give you a foundational understanding of the process of business analysis and will introduce you to a framework that can be used within a variety of industries and organizations. You’ll see how an analyst assesses a business problem, prepares business requirements, and implements [...]

Regression Analysis (Coursera)

The "Regression Analysis" course equips students with the fundamental concepts of one of the most important supervised learning methods, regression. Participants will explore various regression techniques and learn how to evaluate them effectively. Additionally, students will gain expertise in advanced topics, including polynomial regression, regularization techniques (Ridge, Lasso, and [...]

Clustering Analysis (Coursera)

The "Clustering Analysis" course introduces students to the fundamental concepts of unsupervised learning, focusing on clustering and dimension reduction techniques. Participants will explore various clustering methods, including partitioning, hierarchical, density-based, and grid-based clustering. Additionally, students will learn about Principal Component Analysis (PCA) for dimension reduction. Through interactive tutorials and [...]

Classification Analysis (Coursera)

The "Classification Analysis" course provides you with a comprehensive understanding of one of the fundamental supervised learning methods, classification. You will explore various classifiers, including KNN, decision tree, support vector machine, naive bayes, and logistic regression, and learn how to evaluate their performance. Through tutorials and engaging case studies, [...]

Data Wrangling with Python Project (Coursera)

The "Data Wrangling Project" course provides students with an opportunity to apply the knowledge gained throughout the specialization in a real-life data wrangling project of their interest. Participants will follow the data wrangling pipeline step by step, from identifying data sources to processing and integrating data, to achieve a [...]

Data Analysis with Python Project (Coursera)

The "Data Analysis Project" course empowers students to apply their knowledge and skills gained in this specialization to conduct a real-life data analysis project of their interest. Participants will explore various directions in data analysis, including supervised and unsupervised learning, regression, clustering, dimension reduction, association rules, and outlier detection. [...]