Search result for Introduction to data science in python Online Courses & Certifications
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Getting Started with Data Visualization in R
by Collin Paschall- 4.8
Approx. 12 hours to complete
Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. Dataframes and Importing Data in R Introduction to the tidyverse Data import and structure in the tidyverse...
Managing Data Analysis
by Jeff Leek, PhD , Brian Caffo, PhD , Roger D. Peng, PhD- 4.6
Approx. 9 hours to complete
This one-week course describes the process of analyzing data and how to manage that process. 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. Explore datasets to determine if data are appropriate for a given question...
How Google does Machine Learning
by Google Cloud Training- 4.6
Approx. 8 hours to complete
>>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs. Introduction to Course Introduction to ML on Google Cloud Introduction to AI First Python Notebooks in the cloud Python Notebooks in the Cloud Python Notebooks in the Cloud...
Materials Data Sciences and Informatics
by Dr. Surya Kalidindi- 4.5
Approx. 9 hours to complete
More specifically, it is argued that modern data sciences (including advanced statistics, dimensionality reduction, and formulation of metamodels) and innovative cyberinfrastructure tools (including integration platforms, databases, and customized tools for enhancement of collaborations among cross-disciplinary team members) are likely to play a critical and pivotal role in addressing the above challenges. Introduction to PyMKS Materials Knowledge Systems in Python...
Foundations of Sports Analytics: Data, Representation, and Models in Sports
by Wenche Wang , Stefan Szymanski- 4.5
Approx. 49 hours to complete
This course provides an introduction to using Python to analyze team performance in sports. Introduction to Sports Performance and Data Introduction to Data Sources Accessing Data in Python I Accessing Data in Python II Introduction to Sports Data and Plots in Python Introduction to Sports Data and Regression Using Python Introduction to Regression Analysis...
Agile Analytics
by Alex Cowan- 4.8
Approx. 15 hours to complete
Successful analytics are rarely hard to understand and are often startling in their clarity. In this course, developed at the Darden School of Business at the University of Virginia, you'll learn how to build a strong analytics infrastructure for your team, integrating it with the core of your drive to value. Data Science IRL: Intro to the Casino Jack Case...
Capstone: Retrieving, Processing, and Visualizing Data with Python
by Charles Russell Severance- 4.7
Approx. 9 hours to complete
In the capstone, students will build a series of applications to retrieve, process and visualize data using Python. Coming from Python 2 - Encoding Data in Python 3 Identifying Your Data Source - Introduction Spidering and Modeling Email Data - Introduction Accessing New Data Sources - Introduction Visualizing new Data Sources - Introduction...
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Data Processing and Feature Engineering with MATLAB
by Adam Filion , Michael Reardon , Maria Gavilan-Alfonso , Brandon Armstrong , Heather Gorr , Erin Byrne , Brian Buechel , Isaac Bruss , Matt Rich , Nikola Trica , Cris LaPierre- 4.7
Approx. 18 hours to complete
In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB to lay the foundation required for predictive modeling. This intermediate-level course is useful to anyone who needs to combine data from multiple sources or times and has an interest in modeling. Introduction to Module 2: Organizing Your Data...
Developing AI Applications on Azure
by Ronald J. Daskevich, DCS- 4.4
Approx. 16 hours to complete
We'll review standardized approaches to data analytics and you'll receive specific guidance on Microsoft's Team Data Science Approach. Introduction to Artificial Intelligence Links to learn more about python Module 1: Introduction to Artificial Intelligence Microsoft Team Data Science Process Describe AI tools and roles, and the Microsoft Team Data Science Process...
Introduction to Machine Learning Course
by Katie Malone , Sebastian Thrun- 0.0
Timeline Approx. 10 Weeks
Code a Linear Regression in Python with scikit-learn. Implement K-Means in Python and Scikit Learn to find the center of clusters. Apply your knowledge on the Enron Finance Data to find clusters in a real dataset. lesson 10 Feature Scaling Understand how to preprocess data with feature scaling to improve your algorithms....
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