Artificial Intelligence And Data Analytics

As the volume of available business data expands, the winners in tomorrow’s marketplace will be those who can generate insight from information. Yet, many leaders feel daunted by the sheer […]

Updated February 4, 2023

About Course

As the volume of available business data expands, the winners in tomorrow’s marketplace will be those who can generate insight from information. Yet, many leaders feel daunted by the sheer amount of data out there. Many others make the critical mistake of looking for patterns in the data they have, instead of framing productive questions to shape the data they need. Competency in this area is so lacking, a recent Gartner study predicted that by 2020, 80% of organizations will initiate deliberate development programs in data literacy.

Many of the ideas, methods and principles that describe the best business data and analytics practices were explained in this Bootcamp. You will learn how to “think data” the Booth way. They develop the critical and creative reasoning skills needed to frame a data analytics project, collaborate with data specialists, and ultimately make evidenced-based decisions that drive results — without sacrificing speed and agility.

Master the ins and outs of data analytics from foundational topics in data management with Excel and SQL to data cleansing and preprocessing using Python’s highly sought-after functionalities – Pandas and Numpy. Complete your analytics toolkit with the full range of data visualization tools you’ll need to become a compelling data storyteller. Featuring insights into the SQL interview process and a tutorial on date and time value manipulation in Python to give you a strong leg up over the competition.

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What Will You Learn?

  • Develop the key ingredients of a powerful data analytics strategy: a specific business objective, well-developed theories, and a model that points the way to critical data and deep insight.
  • Frame questions to generate data-based insight: Identify specific objectives and related hypotheses to drive data analysis. Avoid biases in interpreting data: Sidestep the common pitfall of unconsciously bending data to support false assumptions and preconceptions.
  • Tell the story of the data: Translate data-driven insights into actionable decisions and drive buy-in by delivering a compelling narrative.
  • Distinguish between various data science related fields
  • Integrate common data science techniques
  • What are the most common data science programming languages
  • Understand the terms traditional and big data
  • Use specific data science tools
  • Become familiar with data science job positions and alternatives
  • Understand Excel best practices
  • Insert and format different types of charts
  • How to use Excel functions
  • Distinguish between the diverse types of data and levels of measurement
  • Calculate confidence intervals
  • Become familiar with the p-value
  • Understand what a distribution is
  • Perform hypothesis testing
  • Basic Python syntax
  • Understand Object-Oriented Programming (OOP)
  • Work with variables, operators, and conditional statements
  • Study Python sequences and iterations
  • Import modules in Python
  • Create basic and advanced charts
  • Create stunning visualization
  • Develop a basic understanding of the pandas library
  • Practice with fundamental programming tools
  • Work with pandas Series and DataFrames
  • Study collecting, cleaning, and preprocessing data

Course Content

MODULE ( 1 )

  • Introduction to AI
  • History of Artificial Intelligence
  • Artificial Intelligence (AI) vs. Machine Learning (ML) vs. Deep Learning (DL)
  • AI Applications
  • AI Basics
  • The benefits of Artificial Intelligence
  • Future of Artificial Intelligence
  • How Do Big Data and Data Analytics Change IT Analysis
  • The Business Analyst Role in Implementing AI-Based Business Solutions
  • The Impact of AL in Three Level of Business Analysis
  • Targeted IT Business Analysis: Analyze Features and User Stories
  • Tactical Business Analysis: Elicit and Prioritize User Requirements
  • Strategic Business Analysis: Prepare for Future Changes

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MODULE ( 5 )

MODULE ( 6 )

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MODULE ( 8 )

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Artificial Intelligence And Data Analytics
Duration 30 hours
118 Lessons

Material Includes

  • After passing the related Bootcamp requirements ( Exam, or Research, Capstone project ) attendees will be qualified to get Certification of achievements Name will be : Global Certified AI Data Analyst ( GCAI | DA )
  • Training Materials in PDF format


  • This course does not assume any prior knowledge of Artificial Intelligence or it’s associated terms. Bring your business and managerial experience - the course will help you do the rest !


  • This program is designed for busy leaders—managers, directors, VPs, and C-suite—with the drive and desire to solve their organization’s critical business challenges.
  • Job titles include senior leaders, mid-level & team leaders, project managers, and directors.
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