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Working in a hands-on learning environment, led by our Python Social Media expert instructor, students will learn about and explore: Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more. Analyze and extract actionable insights from your social data using various Python tools. A highly practical guide to conducting efficient social media analytics at scale.

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Last Updated

January 6, 2021

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Course Description

Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautiful soup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this course, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes.

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Course Curriculum

    • Introduction to the Latest Social Media Landscape and Importance 00:00:00
    • Introducing social graph 00:00:00
    • Delving into social data 00:00:00
    • Understanding the process 00:00:00
    • Working environment 00:00:00
    • Getting the data 00:00:00
    • Analyzing the data 00:00:00
    • Visualizing the data 00:00:00
    • Getting started with the toolset 00:00:00
    • Harnessing Social Data – Connecting, Capturing, and Cleaning 00:00:00
    • APIs in a nutshell 00:00:00
    • Introduction to authentication techniques 00:00:00
    • Parsing API outputs 00:00:00
    • Basic cleaning techniques 00:00:00
    • MongoDB to store and access social data 00:00:00
    • MongoDB using Python 00:00:00
    • Uncovering Brand Activity, Popularity, and Emotions on Facebook 00:00:00
    • Facebook brand page 00:00:00
    • Project planning 00:00:00
    • Analysis 00:00:00
    • Keywords 00:00:00
    • Noun phrases 00:00:00
    • Detecting trends in time series 00:00:00
    • Uncovering emotions 00:00:00
    • How can brands benefit from it? 00:00:00
    • Analyzing Twitter Using Sentiment Analysis and Entity Recognition 00:00:00
    • Scope and process 00:00:00
    • Getting the data 00:00:00
    • Sentiment analysis 00:00:00
    • Customized sentiment analysis 00:00:00
    • Named entity recognition 00:00:00
    • Combining NER and sentiment analysis 00:00:00
    • Campaigns and Consumer Reaction Analytics on YouTube – Structured and Unstructured 00:00:00
    • Scope and process 00:00:00
    • Getting the data 00:00:00
    • Data pull 00:00:00
    • Data processing 00:00:00
    • Data analysis 00:00:00
    • The Next Great Technology – Trends Mining on GitHub 00:00:00
    • Scope and process 00:00:00
    • Getting the data 00:00:00
    • Data pull 00:00:00
    • Data processing 00:00:00
    • Data analysis 00:00:00
    • Scraping and Extracting Conversational Topics on Internet Forums 00:00:00
    • Scope and process 00:00:00
    • Getting the data 00:00:00
    • Data pull and pre-processing 00:00:00
    • Data analysis 00:00:00
    • Demystifying Pinterest through Network Analysis of Users Interests 00:00:00
    • Scope and process 00:00:00
    • Getting the data 00:00:00
    • Data pull and pre-processing 00:00:00
    • Data analysis 00:00:00
    • Social Data Analytics at Scale – Spark and Amazon Web Services 00:00:00
    • Different scaling methods and platforms 00:00:00
    • Topic models at scale 00:00:00
    • Spark on the Cloud – Amazon Elastic MapReduce 00:00:00

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