Search result for Exploratory data analysis steps Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 387 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Market Segmentation Analysis
by Sara Dolnicar , Bettina Grün , Friedrich Leisch- 0.0
-
![]()
![]()
![]()
![]()
![]()
5 Weeks
In this course, we will explore how to leverage statistical concepts into the organisation's segmentation strategy, such as the hierarchical clustering and partitioning methods, exploratory data analysis, biclustering, mixture models, and regression models. The ten steps of a market segmentation analysis and each one's purpose. How to undertake each of the ten steps of market segmentation analysis yourself....
$99
Data Mining Through Cluster Analysis Using Python
by Ermin Dedic- 4.2
-
![]()
![]()
![]()
![]()
![]()
1 hour on-demand video
This course is ideal for those that are interested in data mining, and it is a beginner course. This is a major component of exploratory data mining. If you are interested in data mining, and want to get a taste of how it works, this course is a great introduction!...
$12.99
Scalable Data Analysis in Python with Dask
by Packt Publishing- 3.6
-
![]()
![]()
![]()
![]()
![]()
3.5 hours on-demand video
Data analysts, Machine Learning professionals, and data scientists often use tools such as Pandas, Scikit-Learn, and NumPy for data analysis on their personal computer. In this course, you’ll learn to scale your data analysis. You’ll be working on large datasets and performing exploratory data analysis to investigate the dataset, then come up with the findings from the dataset....
$11.99
Data Science: Sparklyr Basics for Beginners
by Artech Learning, LLC.- 3.7
-
![]()
![]()
![]()
![]()
![]()
1.5 hours on-demand video
Learn to interact with data in Apache Spark through sparklyr and simplify machine learning model implementations. Welcome to this course: Data Science - Sparklyr Basics for Beginners. In the past year, transforming the world using data is typically achieved through disrupting and changing real processes in real industries....
$12.99
Statistics and R
by Rafael Irizarry , Michael Love- 0.0
-
![]()
![]()
![]()
![]()
![]()
4 Weeks
An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences. This course teaches the R programming language in the context of statistical data and statistical analysis in the life sciences. Data Analysis for Life Sciences: 4x: High-Dimensional Data Analysis Genomics Data Analysis: Exploratory Data Analysis...
$249
Business intelligence and data warehousing
by María del Pilar Ángeles- 3.9
-
![]()
![]()
![]()
![]()
![]()
Approx. 10 hours to complete
This course will be completed on six weeks, it will be supported with videos and various documents that will allow you to learn in a very simple way how to identify, design and develop analytical information systems, such as Business Intelligence with a descriptive analysis on data warehouses. The problem of integration and analysis of unstructured data...
Unsupervised Learning
by Mark J Grover , Miguel Maldonado- 4.9
-
![]()
![]()
![]()
![]()
![]()
Approx. 9 hours to complete
You will learn how to find insights from data sets that do not have a target or labeled variable. To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics....
Related searches
Unsupervised Machine Learning
by Mark J Grover , Miguel Maldonado- 4.8
-
![]()
![]()
![]()
![]()
![]()
Approx. 9 hours to complete
You will learn how to find insights from data sets that do not have a target or labeled variable. To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics....
Learn Apache Spark with Python
by Edulearners Technologies- 3.6
-
![]()
![]()
![]()
![]()
![]()
8 hours on-demand video
Apache Spark is the hottest Big Data skill today. And even though Spark is one of the most asked tools for data engineers, also data scientists can benefit from Spark when doing exploratory data analysis, feature extraction, supervised learning and model evaluation. What makes Spark a power tool of Big Data and Data Science?...
$12.99
Supervised Learning: Regression
by Mark J Grover , Miguel Maldonado- 4.8
-
![]()
![]()
![]()
![]()
![]()
Approx. 11 hours to complete
This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Regression techniques in a business setting. To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics....
Previous
