1.
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Introduction to Python [Free Course]
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Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with NumPy.
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Python
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4 Hours
11 Videos
57 Exercises
4,206,184 Learners
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2.
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Data Science for Everyone
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An introduction to data science with no coding involved.
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Non-Technical Course
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2 Hours
15 Videos
48 Exercises
306,312 Learners
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3.
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Introduction to R
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Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.
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R
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4 Hours
62 Exercises
2,250,870 Learners
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4.
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Introduction to Tidyverse
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Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.
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R
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4 Hours
16 Videos
50 Exercises
236,931 Learners
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5.
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Supervised Learning with scikit-learn
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Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.
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Python
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4 Hours
17 Videos
54 Exercises
306,120 Learners
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6.
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Python Programming
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In this track, you’ll learn how to code like a real programmer.
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Python
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Career Track –
24 hours
6 Courses
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7.
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Data Scientist with Python
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Gain the career-building Python skills you need to succeed as a data scientist. No prior coding experience required.
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Python
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Career Track – 88 hours
23 Courses
6 Projects
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8.
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Introduction to SQL [Free Course]
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Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.
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SQL
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4 Hours
1 Video
41 Exercises
1,367,897 Learners
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9.
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Data Engineering for Everyone [FREE Course]
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Discover how data engineers lay the groundwork that makes data science possible. No coding involved!
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SQL
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2 Hours
11 Videos
32 Exercises
119,009 Learners
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10.
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Data Analyst with Python
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In this track, you’ll learn how to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher.
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Python
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Career Track –
66 hours
17 Courses
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11.
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Data Analysis in Excel [Free Course]
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Learn how to analyze data in Excel.
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Excel
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4 Hours
12 Videos
48 Exercises
97,416 Learners
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12.
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Introduction to SQL
More Details
Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.
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SQL
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4 Hours
1 Video
41 Exercises
1,367,907 Learners
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13.
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Introduction to Deep Learning in Python
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Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.
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Python
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4 Hours
17 Videos
50 Exercises
213,821 Learners
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14.
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Unsupervised Learning in Python
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Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
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Python
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4 Hours
13 Videos
52 Exercises
101,003 Learners
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15.
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Data Scientist with R
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Gain the career-building R skills you need to succeed as a data scientist. No prior coding experience required. In this track, you’ll learn how this versatile language allows you to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher.
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R
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Career Track –
88 hours
22 Courses
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16.
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Statistics Fundamentals with R
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Statistics is the study of how best to collect, analyze, and draw conclusions from data. A strong foundation will serve you well, no matter what industry you work in.
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R
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Career Track –
20 hours
5 Courses
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17.
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Introduction to Data Visualization with Matplotlib
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Learn how to create, customize, and share data visualizations using Matplotlib.
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Python
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4 Hours
14 Videos
44 Exercises
105,206 Learners
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18.
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Data Visualization with R
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Bring your data into focus. Develop the invaluable skills you need to analyze and display data using R—essential when communicating insights and discoveries to non-technical stakeholders.
Start this track and learn how to tell better data stories using data visualization.
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R
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Career Track –
12 hours
3 Courses
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19.
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Data Visualization with Python
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Supercharge your data science skills using Python's most popular and robust data visualization libraries. Learn how to use Matplotlib, Seaborn, Bokeh, and others to create beautiful static and interactive visualizations of categorical, aggregated, and geospatial data.
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Python
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Career Track –
16 hours
4 Courses
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20.
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Introduction to Data Visualization with Seaborn
More Details
Learn how to create informative and attractive visualizations in Python using the Seaborn library.
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Python
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4 Hours
14 Videos
44 Exercises
65,413 Learners
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21.
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Finance Fundamentals in R
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By the end of the track, you'll be ready to navigate the world of finance using R—having learned how to work with investment portfolios, calculate measures of risk, and calculate an optimal portfolio based on risk and return.
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R
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Career Track –
28 hours
6 Courses
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22.
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Big Data with R
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R has great ways to handle working with big data including programming in parallel and interfacing with Spark. In this track, you'll learn how to write scalable and efficient R code and ways to visualize it too.
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R
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Career Track –
16 hours
4 Courses
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23.
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Text Mining with R
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Different approaches to organizing and analyzing data of the text variety (books, articles, documents). A primer into regular expressions and ways to effectively search for common patterns in text is also provided.
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R
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Career Track –
16 hours
4 Courses
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24
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Data Science for Business
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This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization's needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You'll also discover ways to analyze and visualize your data through dashboards and A/B tests.
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2 Hours
14 Videos
51 Exercises
66,645 Learners
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25
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Introduction to Tableau
More Details
Get started with Tableau, a widely used business intelligence (BI) and analytics software to explore, visualize, and securely share data.
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Tableau
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6 Hours
24 Videos
60 Exercises
124,960 Learners
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26
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Introduction to Power BI
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Gain a 360° overview of how to explore and use Power BI to build impactful reports.
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Power Bi
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3 Hours
13 Videos
39 Exercises
141,531 Learners
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