Search result for Exploratory data analysis definition Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 213 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Predictive Modeling and Analytics
by Dan Zhang- 3.6
-
![]()
![]()
![]()
![]()
![]()
Approx. 11 hours to complete
Welcome to the second course in the Data Analytics for Business specialization! You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business. Exploratory Data Analysis and Visualizations Why Exploratory Data Analysis is Important Data Cleanup and Transformation...
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
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....
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
Case Studies in Functional Genomics
by Rafael Irizarry , Michael Love , Vincent Carey- 0.0
-
![]()
![]()
![]()
![]()
![]()
5 Weeks
We will also go over quality control of FASTQ files; aligning RNA-seq reads; visualizing alignments and move on to analyzing RNA-seq at the gene-level : counting reads in genes; Exploratory Data Analysis and variance stabilization for counts; count-based differential expression; normalization and batch effects. Data Analysis for Life Sciences: 4x: High-Dimensional Data Analysis...
$149
Related searches
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....
Supervised Machine Learning: Regression
by Mark J Grover , Miguel Maldonado- 4.7
-
![]()
![]()
![]()
![]()
![]()
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....
SQL for Data Science Capstone Project
by Don Noxon- 3.9
-
![]()
![]()
![]()
![]()
![]()
Approx. 35 hours to complete
Data science is a dynamic and growing career field that demands knowledge and skills-based in SQL to be successful. This community of fellow learners will provide additional input to help you refine your approach to data analysis with SQL and present your findings to clients and management. ​Perform descriptive statistics as part of your exploratory analysis...
Previous
