The 2023 Ultimate Big Data Certification Bundle

Learn the basics of coding with Python! All software – including games, apps, websites, and more – is essentially designed to follow instructions. We refer to these instructions as coding and the order and rules that they follow as algorithms. This course will explore these important concepts through Python Turtle. The Turtle library allows you to issue commands to a “turtle” and have the turtle follow them as if it were a pen drawing on paper. You can use it to draw various shapes, fill them in, change their colors, and more – all through easy-to-use programming commands. You’ll also learn how to structure these commands as an algorithm to create a digital picture of a solar system.

• Access 22 lectures & 1 hour of content 24/7
• Understand what programming is
• Move the turtle to draw shapes
• Change shape & background colors
• Control shape fill & spacing
• Define & design algorithms
• Implement algorithms with programming

This course will introduce you to everything that you need to know to get started with data analysis using the Pandas library. To better enhance your understanding, you will not only learn the concepts underlying data analysis but apply them to real-world data – logs of domestic US flights from 2017.

• Access 14 lectures & 1 hour of content 24/7
• Clean data (from dealing with missing/null values, to handling appropriate data types for columns)
• Visualize data using basic line plots & histograms
• Understand basic statistics (including mean & standard deviations, and inferential statistics)
• Implement basic machine learning techniques (using linear regression to learn a line of best fit)

This course will guide you through creating a fully-functional and smart security camera, using a Raspberry Pi or the webcam on your device. The purpose of the application in this course is to detect movement in the video footage and subsequently execute an action, such as sending out an email or an SMS.

Sections covering both the theory and practical applications are included in this course. The theory videos demonstrate the building blocks so that you can understand how it all works. Topics taught in this course include summation notation, image similarity metrics, and video processing. Image similarity is a set of tools that you can use to compare images, which then helps you determine how similar they are.

• Access 22 lectures & 2 hours of content 24/7
• Create a fully-functional smart security camera using Raspberry Pi or a webcam
• Learn about summation notation
• Explore image similarity metrics like sum squared errors, mean squared errors, & structural similarity
• Understand how to perform video processing with Python

Numpy is a library used in python, containing data structures and functions that allow for the usage of powerful and functional arrays and matrices. With the ability to build arrays that are considerably faster than the regular lists in Python, and to make more efficient mathematical computations, Numpy’s applications range from data science to machine learning, game development, and more. This course is your starting point with this tool.

• Access 14 lectures & 1 hour of content 24/7
• Learn how to download & install Anaconda and Jupyter
• Familiarize yourself with creating Numpy arrays, fetch operations, and modification operations
• Explore creating Numpy matrices, fetch operations & modification operations
• Validate your training w/ a certificate of completion

Python is a language that is currently in extremely high-demand, and you can learn it the fun way through this course! With no prior programming experience necessary, this course will demonstrate core concepts you need to program in Python by building your own game, getting you up and running with Python in a way that's both engaging and fun.

• Access 25 lectures & 3 hours of content 24/7
• Create a game similar to Crossy Road or Frogger
• Use the Pygame library to put together your first Python game
• Become familiar with concepts like variables, functions, conditional statements, & loops

In this course, you will be building a photo filter editor that allows you to create filters such as those used on Instagram and Snapchat. This app allows you to load a photo, edit its contrast, brightness, and gray scale. You can also create and apply custom filters using this tool. Theory sections are included, where concepts such as matrices, color models, brightness, contrast, and convolution are explained in detail from a mathematical perspective. Also, practical sections include the installation of the Anaconda development environment, matrix operations, and OpenCV. The photo editor is built from scratch using OpenCV UI.

• Access 23 lectures & 3 hours of content 24/7
• Build a photo filter editor that allows you to create filters such as those used in Instagram & Snapchat
• Create & apply custom filters using the photo fiter editing app
• Learn about matrices, color models, brightness, contrast & convolution
• Know more about Anaconda development environment, matrix operations & OpenCV

Python is an especially valuable tool for visualizing data, and this course will cover a variety of techniques that will allow you to visualize data using popular plotting libraries like Matplotlib, Seaborn, and Bokeh. Beginning with an intro to statistics, you'll extend into a variety of plots that will cover most use-cases.

• Access 23 lectures & 2 hours of content 24/7
• Explore bar charts, line plots, & scatter plots
• Take a deep dive into Matplotlib, Seaborn, & Bokeh
• Discover subplots & how they're used

Master Python skills for gathering and cleaning data from APIs! APIs (Application Programming Interfaces) are pre-built functions and rules that determine how two computers or programs communicate with each other. While this is commonly used to transfer data between them, data from the real world is rarely presented in a way that is perfect for analysis. As such, knowing how to properly extract and clean data is an integral skill for all data scientists.

This course will walk you through how to use Python to retrieve and parse data through the powerful tools provided by APIs. You’ll learn techniques for multiple different file types, and explore how you can manipulate your parsed data to suit your specific needs. No matter your goals, understanding this aspect of data retrieval will give you a better grasp of how data is often transferred and let you navigate the world more informed.

• Access 12 lectures & 1 hour of content 24/7
• Understand what APIs are
• Make URL requests to retrieve data
• Format and parse JSON data
• Work with XML data using BeautifulSoup
• Write data to a CSV file
• Read data from a local file

Python is a high-level, general-purpose language with an emphasis on readability and extensibility. Its versatility provides developers with a robust skill-set that can be adapted to numerous projects, making it a highly desirable language to pursue regardless of where you wind up. Whether your goals are to create simple applications to swap faces, automate meticulous tasks, or develop advanced algorithms to visualize and manage data, this course will provide you with the foundations needed to get started with the language so you can start building your own projects.

• Access 18 lectures & 1 hour of content 24/7
• Set up a Python project
• Utilize variables & operators
• Manage data with lists, tuples, ranges, & dictionaries
• Control program flow with conditionals & loops
• Use functions for program execution
• Create objects & classes for object-oriented programming

Cluster analysis is the process of grouping data that have similar attributes or properties and is incredibly useful in a wide variety of fields and applications, including market analysis and segmentation, medical imaging, recommender systems, geospatial data, anomaly detection, and more. Whether the number of groups (or “clusters”) are predefined or determined by an algorithm, cluster analysis helps to provide you with insight into what data should belong together. This course will provide you with all that you need to get started with cluster analysis.

• Access 17 lectures & 2 hours of content 24/7
• Describe how k-means clustering works
• Perform a k-means cluster analysis using scikit-learn
• Describe how to interpret results from a k-means cluster analysis