Intermediate AI and Data Analytics

This 16-week program is designed for professionals with at least 18 months of work
experience in data analytics. The program covers a wide range of topics to enhance
your understanding and skills in data analytics and AI.

Intermediate AI and Data Analytics

16 Week Program

180 Instructor hours

Courses

  • Identifying Basic Concepts of Data Schemas
  • Understanding Different Data Systems
  • Understanding Types and Characteristics of Data
  • Comparing and Contrasting Different Data Structures, Formats, and
    Markup Languages
  • Explaining Data Integration and Collection Methods
  • Identifying Common Reasons for Cleansing and Profiling Data
  • Executing Different Data Manipulation Techniques
  • And more…

Prerequisites

At least 18 months of work
experience in data analytics.

Class Time Options

Program Objectives

The Intermediate AI and Data Analytics program prepares you are an early to mid-career in data analytics and management.

This program prepares learners to take the CompTIA Data+ credential exam. 

What You Will Learn

  • Identifying Basic Concepts of Data Schemas: Learn the foundational concepts of
    data schemas and their importance in data analytics2.
  • Understanding Different Data Systems: Gain insights into various data systems
    and their applications.
  • Understanding Types and Characteristics of Data: Explore different types of data
    and their unique characteristics.
  • Comparing and Contrasting Different Data Structures, Formats, and Markup
    Languages: Understand the differences between various data structures and
    formats.
  • Explaining Data Integration and Collection Methods: Learn about different
    methods for integrating and collecting data.
  • Identifying Common Reasons for Cleansing and Profiling Data: Discover why
    data cleansing and profiling are essential.
  • Executing Different Data Manipulation Techniques: Master various techniques for
    manipulating data.
  • And more…
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Where Do I Go From Here?

Career Paths after Enterprise AI and Data Analytics:

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