Live training with Minerva Singh, PhD starts on December 14th at 2 PM (EST)

Training duration: 4 hours (Hands-on)

Price with 30% discount

Regular Price: $210.00

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Instructor Bio:

Spatial Data Analysis Expert, Founder at Minerva's Data Lab

Minerva Singh, PhD

Minerva joined the Center for Environmental Policy (CEP), Imperial College London as a Research Fellow in 2018. Before that, she completed a PhD from the University of Cambridge in 2017 where she focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. She holds an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. She has nearly 10 year's experience in conducting academic research at the interface of tropical ecology, data science, earth observation (EO), and artificial intelligence (AI)and published 14 first-author peer-reviewed papers in international journals since 2013 including PLoS One. She has obtained research funding of approximately £275,000 since 2018 and provided research, consultancy, and data science support to startups and industry partners including Treeconomy and Morphobotics LLC. She is a Fellow of the Royal Geographic Society (RGS)and Royal Statistical Society (RSS) as well as serving as an Associate Fellow at the Data Science Institute, Imperial College London. She is also a best selling course-instructor on the online MOOC platform Udemy where she provides online teaching to more than 71,000 students from across the world on machine learning, earth observation, and deep learning related topic

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Learning Objectives

  • Understand the role of unstructured text data (obtained via websites or social media sites) in influencing the financial and business worlds

  • Introduction to web-scraping and extracting data from websites

  • Introduction to social media mining and obtaining textual data from sites such as Twitter and Reddit

  • Pre-processing text data

  • Identify and visualise the dominant topics (5) Identify the dominant sentiments underpinning the texts

  • Implement machine learning and deep learning models on text data

DIFFICULTY LEVEL: INTERMEDIATE

Course Outline

Module 1: Get Started With Text Analysis and Natural Language Processing


* Training Overview 

*How Text Analysis and Natural Language Processing Can Give You An Edge? A Business Case

*Get Your Python Environment Ready

*Introduction To Web-scraping

* Scraping Some Common Websites For Information

* Obtaining Tweets (Without an API)

* Obtaining Reddit Posts Relating To a Topic

* Different Sources of Newspaper Headlines 



Module 2: Pre-Processing Text Data


*Basic Text Cleaning Workflow

* Text Cleaning and Preprocessing Using NTLK

*Text Cleaning and Preprocessing With Scikit

* Text Cleaning and Preprocessing With TextBlob

* Some Other Text Cleaning and Pre-processing Strategies

* Text Summarisation With Spacy

* Dealing With Dates



Module 3: Exploratory Data Analysis (EDA) For Text Data


* Quantify Social Media Post Lengths

* Which Are The Most Popular Hashtags

* Introduction To Wordclouds

*Identify The Most important Topics With Gensim

* Business Use Case Study: Extract The Most important Topics From Yelp Reviews With Spacy



Module 4: Sentiment Analysis


*Identify the Polarity of Text

* Polarity: Positive or Negative

* VADER Sentiment Analysis

* Business Use Case Study: Identify The Most Dominant Sentiments Of Reddit Forum WallStreetBets wrt Meme Stocks


Module 5: Artificial Intelligence (AI)  Analysis For Text Data


* Identify Text Clusters With Unsupervised Learning

* Text Sentiment Classification With Machine Learning

* Text Sentiment Classification With Deep Learning

* Business Use Case Study: Predicting Price Action On the Basis Of Social Media Sentiments 

Course Abstract

Do you want to harness the power of social media to make financial decisions? Are you looking to gain an edge in the fields of retail, online selling, real estate and geolocation services? Do you want to develop cutting-edge analytics and visualizations to take advantage of the millions of Twitter and Reddit posts that appear each day? Gaining proficiency in social media mining can help you harness the power of the freely available data and information on the world wide web (including popular social media sites such as Twitter) and turn it into actionable insights MY COURSE IS A HANDS-ON TRAINING WITH REAL PYTHON SOCIAL MEDIA MINING- You will learn to carry out text analysis and natural language processing (NLP) to gain insights from unstructured text data, including tweets My course provides a foundation to carry out PRACTICAL, real-life social media mining. By taking this course, you are taking an important step forward in your data science journey to become an expert in harnessing the power of social media for deriving insights and identifying trends. This course will help you gain fluency both in the different aspects of text analysis and NLP working through a real-life example of cryptocurrency tweets, Wall Street Bet Reddit posts, restaurant reviews, and financial news using a powerful clouded based python environment called GoogleColab

What background knowledge you should have?

  • Prior exposure to python programming concepts

  • Familiarity with Jupyter notebooks

  • A desire to learn about practical text analysis and natural language processing (NLP)

What is included in your ticket?

  • Access to live training and QA session with the Instructor

  • Access to the on-demand recording

  • Certificate of completion

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