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Introduction to Analytics and Artificial Intelligence

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Introduction to Analytics and Artificial Intelligence

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Introduction to Analytics and Artificial Intelligence

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Contents

  • 1. Analytics Beginnings
    • Free Introduction
      02m 29s
    • Free History of Analytics
      12m 33s
    • Free Introduction to Data and Big Data
      06m 13s
    • Data Mining - Part 1
      11m 10s
    • Data Mining - Part 2
      09m 56s
    • Business Intelligence - Part 1
      09m 49s
    • Business Intelligence - Part 2
      09m 29s
    • 4 Types of Analytics
      09m 14s
    • Types of Analytics Methods
      13m 05s
  • 2. Artificial Intelligence
    • Artificial Intelligence - Part 1
      09m 57s
    • Artificial Intelligence - Part 2
      09m 23s
    • Machine Learning - Part 1
      10m 48s
    • Machine Learning - Part 2
      10m 23s
    • Deep Learning
      09m 15s
    • Other AI Analytics Techniques - Part 1
      09m 34s
    • Other AI Analytics Techniques - Part 2
      09m 11s
    • Other AI Analytics Techniques - Part 3
      08m 28s
    • Conclusion
      08m 07s
  • 3. Exercise & Course Close
    • Exercise 1
      12m 12s
    • Course Close
      00m 37s
  • Description
  • Course Resources
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Introduction to Analytics and Artificial Intelligence

  • DURATION: 3.1 hours
  • VIDEOS: 20
  • LEVEL: Beginner

The richest data store is only as good as your ability to search, sort, analyze, and present the data within it. This introduction to analytics and artificial intelligence (AI) course will give students a broad overview of the theory and practice of data analytics and the many ways in which AI contributes to it.

Your instructor will begin with a brief history of data analytics and then proceed into discussions of data warehouses, data mining, business intelligence, machine learning, and other emerging AI techniques to make sense of big data.

Students will learn how data is captured, cleansed, analyzed, and presented on business intelligence dashboards that captivate and persuade an audience. “It is a capital mistake to theorize before one has data,” Sherlock Holmes once said.

Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles, this course will give you the foundation you are looking for.

This program includes 3 hours of instruction and a practice-based assessment, which will help students simulate real-world data analytics scenarios that are critical for success in today’s increasingly complex workplace.

Students will gain:

  • A brief overview of the history of analyzing data, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.
  • A look at data stores, which are growing exponentially, and the challenges of wrangling “big data.”
  • Understanding of data mining—what it entails, different approaches, and who’s leading the way.
  • A two-part discussion of business intelligence, including the principles of sound dashboard design and data presentation.
  • The key differences between the four types of analytics—diagnostic, descriptive, predictive, and prescriptive—and how they relate to and build upon each other and how they apply to various industries.
  • An overview of specific analytics processes and models.
  • A first look at AI, its evolution, its functions, and what it can do for businesses today.
  • An exploration of machine learning—how systems can learn from data, identify patterns, and make decisions with little human intervention.
  • A survey of deep learning technologies, including a variety of neural networks.
  • An overview of the most important machine learning data modeling techniques
  • A practical and honest appraisal of the analytics and AI landscape today and moving forward, including the tremendous promise and the potential pitfalls.
  • Resources for continued study on these topics.

Introduction to Analytics and Artificial Intelligence

The course comes with course and exercise files compressed into .zip format. You will need to download the .zip file to your PC or Mac (the files are not compatible with a mobile device) and unzip it. Once unzipped, all of the exercise files will reside in one folder.

Click on the below links to download the zip files.

  • Introduction to Analytics and AI Course Files
  • Introduction to Analytics and AI Exercise Files

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