Search result for Courses in data science Online Courses & Certifications
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Programming for Data Science with R
by Josh Bernhard , Derek Steer , Juno Lee , Richard Kalehoff , Karl Krueger- 0.0
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3 Months
The Programming for Data Science Nanodegree program offers you the opportunity to learn the most important programming languages used by data scientists today. However, as a graduate of this program, you will be proficient in the programming skills used in many data analysis and data science roles, including R, SQL, Terminal, and Git....
Data Science in Real Life
by Brian Caffo, PhD , Jeff Leek, PhD , Roger D. Peng, PhD- 4.4
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Approx. 7 hours to complete
Have you ever had the perfect data science experience? This is a focused course designed to rapidly get you up to speed on doing data science in real life. 1, Describe the “perfect” data science experience Data science in the ideal versus real life Part 1 Data science in the ideal versus real life Part 2...
Business Analytics
by Josh Bernhard , Dana Sheahan , Mat Leonard , Derek Steer , Sam Nelson- 0.0
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3 Months
These skills are also a great foundation to a career in data analysis and data science. In this program, you’ll learn foundational data skills that apply across functions and industries. We have more courses that will pick up from where this course leaves off to help you become ready for a career in data science....
Data Science Interview Prep
by Arpan Chakraborty , Jimmy Lafontaine Rivera- 0.0
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Approx. 1 week
In this course, you'll learn how to approach an interview not as a test, but a showcase. Prepare for data science interviews by practicing data analysis, machine learning, and data structure and algorithms questions....
Free
Advanced Data Science Capstone
by Romeo Kienzler- 4.6
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Approx. 9 hours to complete
This project completer has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case where he justifies architectural decisions, proves understanding the characteristics of different algorithms, frameworks and technologies and how they impact model performance and scalability....
Getting Started with Data Visualization in R
by Collin Paschall- 4.8
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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. Functions in R Dataframes and Importing Data in R Data import and structure in the tidyverse...
SQL for Data Science
by Sadie St. Lawrence- 4.6
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Approx. 14 hours to complete
This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes....
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Introduction to Data Science in Python
by Christopher Brooks- 4.5
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Approx. 31 hours to complete
This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python. 50 years of Data Science, David Donoho (Optional) Describe common Python functionality and features used for data science...
Advanced R Programming
by Roger D. Peng, PhD , Brooke Anderson- 4.3
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Approx. 18 hours to complete
This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. You will also be able to define new data types in R and to develop a universe of functionality specific to those data types to enable cleaner execution of data science tasks and stronger reusability within a team....
AI Workflow: Business Priorities and Data Ingestion
by Mark J Grover , Ray Lopez, Ph.D.- 4.3
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Approx. 8 hours to complete
Specifically, the courses in this specialization are meant for practicing data scientists who are knowledgeable about probability, statistics, linear algebra, and Python tooling for data science and machine learning. Know the advantages of carrying out data science using a structured process Explain where data science and data engineering have the most overlap in the AI workflow...
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