LIVE TRAINING
SAVE THE DATE: December 14th, 2021 @ 2 pm EST
Dr Singh, a fellow of the Royal Statistical Society (RSS), Associate Fellow at the Data Science Institutue, Imperial College London. Her specialties ranges from deep learning (Tensorflow, Keras), machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among many others.
LIVE TRAINING: Introduction to PYTHON for Programming
October 12th @12 PM EST
Price: $147
Regular price $210, discounted 10%
4 hour immersive session
Hands-on training with Q&A
Recording available on-demand
Certification of Completion
30% Discount Ends in:
Subscribe and get an additional 10% to 35% off ALL live training session
Pricing: $189
Regular price $210, discounted 10%
4 hour immersive session
Hands-on training with Q&A
Recording available on-demand
Certification of Completion
10% Discount Ends in:
Subscribe and get an additional 10% to 35% off ALL live training session
Meet Your Instructor
Minerva Singh
Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. As part of her research, she carried out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. These are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.
Course Overview
What’s the plan?
By the end of this live, hands-on, course, you will have 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.
Course Outline
What’s the plan?
Matt Harrison has been working with Python and data since 2000. He has a computer science degree from Stanford. He has worked at many amazing companies, created cool products, wrote a couple books, and taught thousands Python and Data Science. Currently, he is working as a corporate trainer, author, and consultant through his company Metasnake, which provides consulting and teaches corporations how to be effective with Python and data science.
Course Overview
Python is a powerful tools that XXX
Join the live session with Minerva Singh
SAVE 10%Course Outline
Module 1:
Get Started With Text Analysis and Natural Language Processing
Module 2:
Pre-Processing Text Data
Module 3:
Exploratory Data Analysis (EDA) For Text Data
Module 4:
Sentiment Analysis
Module 5:
Artificial Intelligence (AI) Analysis For Text Data
- 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
- 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
- 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
- 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
- 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
Key Details
DATE
TIME:
DURATION:
LEVEL:
DECEMBER 14Th, 2021
TIME: 2 PM EST, 11 AM PST
4 HOURS
INTERMEDIATE
Prerequisites
*Python familiarity (For Text Analysis and NLP, will use: scikit-Learn, Spacy, Gensim, NTLK and TextBlob). For webscraping and social media mining, BeautifulSoup, snscrape, twint will be used.
Upcoming Live Training
January 11, 2022
In this course, you will discover how to use Kubeflow to create a pipeline that retrains a machine learning model automatically and then redeploy the new model on top of an existing one. This process is a complex case that is common in MLOps. Allowing the company to automate the retraining and redeployment process. This material is based on 100% open-source tools that are most popular today in MLOps.
Upcoming Live Training
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