Search result for Data analysis methods qualitative Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 570 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Experimental Design Basics
by Douglas C. Montgomery- 4.7
-
![]()
![]()
![]()
![]()
![]()
Approx. 13 hours to complete
The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Portland Cement Data Example Florescence Data Example Unit 3: Experiments with a Single Factor - The Analysis of Variance...
Financial Analysis of Insurance Companies – Industry Overview and Analysis of Financial and Regulatory Reporting
by Jack Farmer- 0.0
-
![]()
![]()
![]()
![]()
![]()
3 Weeks
Want to gain a solid understanding of the unique analysis methods needed to assess the financial strength and operating performance of insurance companies in the US and Europe? Next, we’ll look at other sources of financial data and at the different accounting methods and standards that you will encounter when evaluating insurance companies....
$199
Data – What It Is, What We Can Do With It
by Jennifer Bachner, PhD- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 11 hours to complete
This course introduces students to data and statistics. We’ll talk about how analysts use data for descriptive, causal and predictive inference. Data and Theories Big Data is Not About the Data! Measures of the Center of the Data Measures of the Location of the Data Measures of the Spread of the Data...
Supervised Learning: Classification
by Mark J Grover , Miguel Maldonado- 4.9
-
![]()
![]()
![]()
![]()
![]()
Approx. 11 hours to complete
The hands-on section of this course focuses on using best practices for classification, including train and test splits, and handling data sets with unbalanced classes. This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Classification techniques in a business setting. Modeling Approaches: Nearing Neighbor Methods...
Supervised Machine Learning: Classification
by Mark J Grover , Miguel Maldonado- 4.9
-
![]()
![]()
![]()
![]()
![]()
Approx. 11 hours to complete
The hands-on section of this course focuses on using best practices for classification, including train and test splits, and handling data sets with unbalanced classes. This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Classification techniques in a business setting. Modeling Approaches: Nearing Neighbor Methods...
Complete linear algebra: theory and implementation in code
by Mike X Cohen- 4.8
-
![]()
![]()
![]()
![]()
![]()
33.5 hours on-demand video
Improve your coding skills! You do need to have a little bit of coding experience for this course (I do not teach elementary Python or MATLAB), but you will definitely improve your scientific and data analysis programming skills in this course. Understand data compression and dimension-reduction (PCA, SVD, eigendecomposition)....
$13.99
Basics of Statistical Inference and Modelling Using R
by Elena Moltchanova- 0.0
-
![]()
![]()
![]()
![]()
![]()
6 Weeks
Basics of Statistical Inference and Modelling Using R is part one of the Statistical Analysis in R professional certificate. Exploratory data analysis and data visualisation using R. Analysis of Variance (ANOVA) and post-hoc tests using R. Multivariate analysis using linear regression and analysis of variance with covariates (ANCOVA)....
$249
Related searches
Foundations of Sports Analytics: Data, Representation, and Models in Sports
by Wenche Wang , Stefan Szymanski- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 49 hours to complete
This course does not simply explain methods and techniques, it enables the learner to apply them to sports datasets of interest so that they can generate their own results, rather than relying on the data processing performed by others. Regression Analysis - Intro to Cricket Data Using regression analysis - an example with NBA data...
Python Data Science with Pandas: Master 12 Advanced Projects
by Alexander Hagmann- 4.3
-
![]()
![]()
![]()
![]()
![]()
15.5 hours on-demand video
Welcome to the first advanced and project-based Pandas Data Science Course! Import (complex and nested) Data from SQL Databases. Store (complex and nested) Data in JSON files. Store (complex and nested) Data in SQL Databases. Explanatory Data Analysis and Data Presentation with advanced Visualization Tools (advanced Matplotlib & Seaborn). Explanatory Data Analysis with large real-world Datasets...
$14.99
Stochastic Processes: Data Analysis and Computer Simulation
by Ryoichi Yamamoto , John J. Molina- 0.0
-
![]()
![]()
![]()
![]()
![]()
6 Weeks
This course is an introduction to stochastic processes through numerical simulations, with a focus on the proper data analysis needed to interpret the results. At the end of the course, we will analyze the dynamical data of more complicated systems, such as financial markets or meteorological data, using the basic theory of stochastic processes. Application: analysis of financial data...
$49
Previous
