You don’t need to be a programming prodigy to get started in data science. Easy to use and highly accessible, Plotly is library in Python that lets you create complex plots and graphs with minimal programming know-how. From creating basic charts to adding motion to your visualizations, this course will walk you through the Plotly essentials with hands-on examples that you can follow.
- Access 28 lectures & 2 hours of content 24/7
- Learn how to build line charts, bar charts, histograms, pie charts & other basic visualizations
- Explore visualizing data in more than two dimensions
- Discover how to add motion to your graphs
- Work w/ plots on your local machine or share them via the Plotly Cloud
Before a data scientist can properly analyze their data, they must first visualize it and understand any relationships that might exist in the information. To this end, many data professionals use Matplotlib, an industry-favorite Python library for visualizing data. Highly customizable and packed with powerful features for building graphs and plots, Matplotlib is an essential tool for any aspiring data scientist, and this course will show you how it ticks.
- Access 30 lectures & 3 hours of content 24/7
- Explore the anatomy of a Matplotlib figure & its customizable parts
- Dive into figures, axes, subplots & more components
- Learn how to draw statistical insights from data
- Understand different ways of conveying statistical information
Bokeh is an open-source, easy-to-use and highly accessible library in Python which allows even developers with just basic programming ability to get up and running with complex plots and graphs. Far easier to use than competing frameworks such as Matplotlib, Bokeh is especially compelling because of how easy it is to build interactivity into your visualizations. Explore relationships in your data without in-depth programming knowledge, extract insights which can be used for further analysis on your data.
- Access 21 lectures & 1 hour of content 24/7
- Structure your visuals in the right format
- Customize the look & feel of basic line plots
- Plot stacked graphs & bar charts w/ multi-level data
- Visualize nodes & edges in network graphs
- Use Bokeh’s built-in libraries to view maps & plot geo-location data
- Add interactivity to legends, tooltips, & toolbars, and use plot tools to play w/ and modify data
- Use the model-view-controller paradigm to separate data & visualization to build custom, interactive plots
From tech to medicine and finance, data plays a pivotal role in guiding today’s businesses. But, it needs to be properly broken down and visualized before you can get any sort of actionable insights. That’s where Seaborn comes into play. Designed for enhanced data visualization, this Python-based library helps bridge the gap between vast swathes of data and the valuable insights they contain. This course acts as your Seaborne guide, walking you through what it can do and how you can use it to display information, find relationships, and much more.
- Access 16 lectures & 1 hour of content 24/7
- Familiarize yourself w/ Seaborn via hands-on examples
- Discover Seaborn’s enhanced data visualization capabilities
- Explore histograms, linear relationships & more visualization concepts
Today’s companies collect and utilize a staggering amount of data to guide their business decisions. But, it needs to be properly cleaned and organized before it can be put to use. Enter NumPy, a core library in the Python data science stack used by data science gurus to wrangle vast amounts of multidimensional data. This course will take you through NumPy’s basic operations, universal functions, and more as you learn from hands-on examples.
- Access 27 lectures & 2 hours of content 24/7
- Familiarize yourself w/ NumPy’s basic operations & universal functions
- Learn how to properly manage data w/ hands-on examples
- Validate your training w/ a certificate of completion
It’s no secret that data scientists stand to make a pretty penny in today’s data-driven world; but if you’re keen on becoming one, you’ll need to master the appropriate tools. Pandas is one of the most popular of the Python data science libraries for working with mounds of data. By expressing data in a tabular format, Pandas makes it easy to perform data cleaning, aggregations and other analyses. Built around hands-on demos, this course will walk you through using Pandas and what it can do as you take on series, data frames, importing/exporting data, and more.
- Access 23 lectures & 2.5 hours of content 24/7
- Explore Panda’s built-in functions for common data manipulation techniques
- Learn how to work with data frames & manage data
- Deepen your understanding w/ example-driven lessons
Big Data sounds pretty daunting doesn’t it? Well, this course aims to make it a lot simpler for you. Using Hadoop and MapReduce, you’ll learn how to process and manage enormous amounts of data efficiently. Any company that collects mass amounts of data, from startups to Fortune 500, need people fluent in Hadoop and MapReduce, making this course a must for anybody interested in data science.
- Access 72 lectures & 13 hours of content 24/7
- Set up your own Hadoop cluster using virtual machines (VMs) & the Cloud
- Understand HDFS, MapReduce & YARN & their interaction
- Use MapReduce to recommend friends in a social network, build search engines & generate bigrams
- Chain multiple MapReduce jobs together
- Write your own customized partitioner
- Learn to globally sort a large amount of data by sampling input files
Hive helps you leverage the power of distributed computing and Hadoop for Analytical processing. Its interface is similar to SQL and this course will help you fill in all the gaps between SQL and what you need to use Hive. It’s an end-to-end guide for using Hive: whether you’re an analyst who wants to process data or an engineer who needs to build custom functionality or optimize performance, everything you need is right here.
- Access 73 lectures & 13 hours of content 24/7
- Write complex analytical queries on data in Hive & uncover insights
- Leverage ideas of partitioning, bucketing to optimize queries in Hive
- Customize Hive w/ user-defined functions in Java & Python
- Understand what goes on under the hood of Hive w/ HDFS & MapReduce
Python is a general-purpose programming language which can be used to solve a wide variety of problems, be they in data analysis, machine learning, or web development. This course lays a foundation to start using Python, which considered one of the best first programming languages to learn. Even if you’ve never even thought about coding, this course will serve as your diving board to jump right in.
- Access 28 lectures & 3 hours of content 24/7
- Gain a fundamental understanding of Python loops, data structures, functions, classes, & more
- Learn how to solve basic programming tasks
- Apply your skills confidently to solve real problems
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