Search result for Exploratory data analysis process Online Courses & Certifications
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Exploratory Data Analysis
by Roger D. Peng, PhD , Jeff Leek, PhD , Brian Caffo, PhD- 4.7
Approx. 55 hours to complete
This course covers the essential exploratory techniques for summarizing data. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. Exploratory Graphs (part 1) Exploratory Graphs (part 2) Welcome to Exploratory Data Analysis Exploratory Data Analysis with R Book Apply cluster analysis techniques to locate patterns in data...
Managing Data Analysis
by Jeff Leek, PhD , Brian Caffo, PhD , Roger D. Peng, PhD- 4.6
Approx. 9 hours to complete
We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results....
Advanced Manufacturing Process Analysis
by Rahul Rai- 4.6
Approx. 13 hours to complete
Gain insights into the best ways to collect, prepare and analyze data, as well as computational platforms that can be leveraged to collect and process data over sustained periods of time. Introduction to Advanced Manufacturing Process Analysis Introduction to Advanced Manufacturing Process Analysis The Data Analysis Process Resources: Data Analysis: Value and Process...
Applied Data Science Capstone
by Joseph Santarcangelo , Alex Aklson- 4.7
Approx. 10 hours to complete
This capstone project course will give you a taste of what data scientists go through in real life when working with data. You will learn about location data and different location data providers, such as Foursquare. Exploratory Data Analysis (EDA) Exploratory Data Analysis Overview Check Points: Exploratory Analysis Using SQL Exploratory Data Analysis using SQL Exploratory Data Analysis...
Data Analysis and Visualization
by Peter Baumgartner , Brittany O'Dea- 4.3
Approx. 11 hours to complete
By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python)....
Statistics for Genomic Data Science
by Jeff Leek, PhD- 4.2
Approx. 9 hours to complete
An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University. Exploratory Analysis (9:21) Exploratory Analysis in R Part I (7:22) Exploratory Analysis in R Part II (10:07) Exploratory Analysis in R Part III (7:26)...
Intro to Data Analysis
by Caroline Buckey- 0.0
Timeline Approx. 6 Weeks
lesson 1 Data Analysis Process Learn about the data analysis process. lesson 2 NumPy and Pandas for 1D Data Start learning to use NumPy and Pandas to make the data analysis process easier. lesson 4 Investigate a Dataset Use NumPy and Pandas to go through the data analysis process on one of a list of recommended datasets....
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Six Sigma Advanced Define and Measure Phases
by Christina Scherrer, PhD , Gregory Wiles, PhD , Bill Bailey, PhD- 4.8
Approx. 15 hours to complete
This course will provide you with the advanced knowledge of team dynamics and performance, process analysis, probability, statistics, statistical distributions, collecting and summarizing data, measurement systems analysis, process and performance capability, and exploratory data analysis associated with Six Sigma and Lean. PROCESS AND PERFORMANCE CAPABILITY & EXPLORATORY DATA ANALYSIS Exploratory Data Analysis - Recommended Reading...
IBM Data Analyst Capstone Project
by Ramesh Sannareddy , Rav Ahuja- 4.6
Approx. 13 hours to complete
You will undertake the tasks of collecting data from multiple sources, performing exploratory data analysis, data wrangling and preparation, statistical analysis and mining the data, creating charts and plots to visualize data, and building an interactive dashboard. Hands-on Lab 2: Collecting Data Using APIs Hands-on Lab 4: Collecting Data Using Web Scraping Exploratory Data Analysis...
Statistics with R Capstone
by Merlise A Clyde , Colin Rundel , David Banks , Mine Çetinkaya-Rundel- 4.6
Approx. 6 hours to complete
A large and complex dataset will be provided to learners and the analysis will require the application of a variety of methods and techniques introduced in the previous courses, including exploratory data analysis through data visualization and numerical summaries, statistical inference, and modeling as well as interpretations of these results in the context of the data and the research question....