High Speed Data Analysis for the REAL WORLD
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 2.01 GB
Genre: eLearning Video | Duration: 62 lectures (4 hour, 49 mins) | Language: English

Secret weapons for real world data gathering, extraction and analysis, ready to use NOW!

What you'll learn

    Enterprise level Text Data Analysis
    Natural Language Processing using Python
    NLTK: A leading platform for building Python programs to work with human language data.
    Web Scraping (Gathering and extracting text data from blogs, articles or text content sites and pages)
    Named-entity Recognition. (How to extract key pieces of information from text sources)
    Extract text from .pdf documents for analysis
    Pandas Dataframe manipulation and export to pdf
    Import and Export Virtual Machines with Oracle VirtualBox
    Text tokenization for word and sentence analysis
    spaCy: NLP library designed to help you do real work - to build real products, or gather real insights.
    Optical Character Recognition (OCR) for text extraction from images using pytesseract
    Generate .pdf reports of your analysis to share instantly.
    Extract text from MS Word documents for analysis

Requirements

    Basic understanding of computers
    System Requirements: Processor: 2 gigahertz (GHz) or faster. RAM: 8 GB and Free hard disk space: 55 GB. Graphics card: Microsoft DirectX 9 graphics device with WDDM driver.
    Reliable high speed internet

Description

THIS IS THE ULTIMATE GET STARTED FAST COURSE. Make no mistake data is the new gold. The amount of data being generated is exploding, those that can mine and analyze it for actionable decisions ARE WINNING. That is what you will learn in this course. We deploy a "Use Case" approach to not only give you a real world situation but show you step by step how to apply various Natural Language Processing methods or tools to extract the data you need for a fast accurate solution. NO SUBSCRIPTIONS, NO software to buy, just the tools provided to you in this course!

Why Data Analysis:

"Over 2.5 quintillion bytes of data are created every single day, and it's only going to grow from there. Today, it's estimated that 1.7MB of data will be created every second for every person on earth."

TOP 10 Reasons YOU should learn Data Analysis:

1. Take this course to unlock opportunities you never knew about.

2. You already use Natural Language Processing (NLP) applications without even knowing it (Spell Checkers, Chatbots, Siri, Alexa, Resume sites, News aggregators)

3. The Banking industry uses NLP data analysis for various loan application processing.

4. Investors use NLP data analysis for financial statement insights.

5. Marketers use NLP data analysis for advertising/content optimization.

6. Healthcare insurers use NLP data analysis for faster claims processing.

7. Higher Education schools and institutes use NLP data analysis for plagiarism checking.

8. Brand managers use NLP to monitor customer feedback and mood towards certain brands.

9. Law Firms use NLP data analysis for contract auditing.

10. The Luxury industry uses NLP data analysis to provide better purchase recommendations.

**** Can you afford NOT TO cash in on the future?

* Add a new dimension to your Search Engine Optimization (With better keywords)

*Get higher conversions from your sales scripts. (By understanding why ones perform and others do not)

*Increase the accuracy of your opponent profile. (Isolate words and phrases used most)

All of this falls under the Domain of Natural Language Processing. Natural Language Processing, or NLP for short, is broadly defined as the automatic manipulation of natural language, like speech and text, by software. But that doesn't even come close to what you can do with NLP and a variety of Data. You will become familiar with some basics in the Python programming language and in the end, you will have a portable (virtual machine) personal arsenal of tools to leverage across any number of text data sources. Giving you and or your organization the edge now and moving forward.

*Get the upper hand in Content Generation. (Optimized Content based on Analysis)

As an organizational leader, If you wanted to generate insights for text data, this course is for you. If you are involved in Market research this course is for you. If you conduct any form of competitive analysis this course is for you. Political campaign strategists needing a deeper understanding of the opponent, you guessed it. THIS COURSE IS FOR YOU!

*Level-Up in your Career with NOW SKILLS! (Instantly ADD MORE VALUE)

What you will learn are HIGHLY transferable skills applicable across a wide range of industries beyond I.T. (Healthcare, Legal, Insurance, Politics and Business). Whether you are changing careers, a student, an MBA or in a leadership position; your analysis skills will improve tremendously!

Are there other uses for what you learn? ABSOLUTELY. One example that was sent to me, was from a songwriter. Yes, you read that correctly, a songwriter using data analysis! This individual compiled a collection of the lyrics of the top selling songs in his genre for the past 10 years. Using the Token frequency and TF-IDF scripts to isolate most used and highest weighted words across all lyrics in an effort to write songs with an increased probability for success. OF_NOTE: He did acknowledge that were more factors that play into this, but he was determined to capture every advantage possible.

"To be able to do data analysis like this by myself, gives me a broader range of thought and creativity as to what is possible for my music"

C.H.

As a BONUS you will                                                                                                                                                                                                          be provided a product or service recommendation script!

**** Unlike any other course I am aware of, YOU get a data analysis Virtual Machine ready to run out of the box! ****

Who this course is for:

    Python developer interested in Data Analysis
    Anyone interested in data science and data analysis for use in practical application not theory.
    Those involved in marketing or promotion of products or services.
   

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