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CertPREP Courseware: IT Specialist Computational Thinking - Instructor-Led

CertPREP Courseware: IT Specialist Computational Thinking - Instructor-Led
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Description
This instructor-led CertPREP IT Specialist Computational Thinking course focuses on knowledge needed to describe data storage; bits and their storage; representing information in bit patterns; data and programming; data manipulation; arithmetic/logic; programming data manipulation; algorithms; the concept of an algorithm; algorithm representation; algorithm discovery; iterative structures; recursive structures; efficiency and correctness; programming languages; historical perspective of programming languages; traditional programming concepts; procedural units; object-oriented programming; software engineering; the software engineering discipline; the software life cycle; software engineering methodologies; modularity; tools of the trade; quality assurance; documentation; the human-machine interface; data abstractions; basic data structures; related concepts; customized data types; classes and objects; abstract models; database systems; database fundamentals; the relational model; object-oriented databases; traditional file structures; data mining; social impact of database technology; artificial intelligence; intelligence and machines; perception; reasoning; theory of computation; functions and their computation; Turing machines; universal programming languages; a non-computable function; and complexity of problems. Designed for professionals in both non-technical or technical roles, this course focuses on the critical thinking and decision-making skills needed for success at the IT Specialist level.

The goal of this course is to provide you with all the tools you need to prepare for the IT Specialist Computational Thinking exam to increase your chances of passing the exam on your first try.

Course components:
  • Lessons
  • Video learning
  • MeasureUp Practice Test for IT Specialist Computational Thinking (INF-308). Practice Mode with remediation and Certification mode to simulate the test day experience.
  • Labs

Duration: 1 day

Audience: Participants who are ready to demonstrate their understanding of computational thinking, including decomposing problems, collecting and analyzing data, recognizing patterns in data, representing data through abstractions, and automating solutions through algorithmic thinking.

Prerequisites:
     
  • 0-1 years of experience working in the field
  • Limited to no experience with computational thinking concepts

Required course materials: One seat of instructor-led CertPREP IT Specialist Computational Thinking (INF-308) Courseware for each student.

Course objectives:
  Upon successful completion of this course, students should be able to:
      
  • Describe Data Storage
  • Describe Data Manipulation
  • Describe Algorithms
  • Describe Programming Languages
  • Describe Software Engineering
  • Describe Data Abstractions
  • Describe Database Systems
  • Describe Artificial Intelligence
  • Describe the Theory of Computation
Chapter 1: Data Storage
  • 1.1 Bits and Their Storage
  • 1.4 Representing Information as Bit patterns
  • 1.8 Data and Programming
Chapter 2: Data Storage
  • 2.4 Arithmetic/Logic
  • 2.6 Programming Data Manipulation
Chapter 5: Algorithms
  • 5.1 The Concept of an Algorithm
  • 5.2 Algorithm Representation
  • 5.3 Algorithm Discovery
  • 5.4 Iterative Structures
  • 5.5 Recursive Structures
  • 5.6 Efficiency and Correctness
Chapter 6: Programming Languages
  • 6.1 Historical Perspective
  • 6.2 Traditional Programming Concepts
  • 6.3 Procedural Units
  • 6.5 Object-Oriented Programming
Chapter 7: Software Engineering
  • 7.1 The Software Engineering Discipline
  • 7.2 The Software Life Cycle
  • 7.3 Software Engineering Methodologies
  • 7.4 Modularity
  • 7.5 Tools of the Trade
  • 7.6 Quality Assurance
  • 7.7 Documentation
  • 7.8 The Human-Machine Interface
Chapter 8: Data Abstractions
  • 8.1 Basic Data Structures
  • 8.2 Related Concepts
  • 8.5 Customized Data Types
  • 8.6 Classes and Objects
  • 8.7 Abstract Models
Chapter 9: Database Systems
  • 9.1 Database Fundamentals
  • 9.2 The Relational Model
  • 9.3 Object-Oriented Databases
  • 9.5 Traditional File Structures
  • 9.6 Data Mining
  • 9.7 Social Impact of Database Technology Chapter 11: Artificial Intelligence
    • 11.1 Intelligence and Machines
    • 11.2 Perception
    • 11.3 Reasoning
    Chapter 12: Theory of Computation
    • 12.1 Functions and their Computation
    • 12.2 Turing Machines
    • 12.3 Universal Programming Languages
    • 12.4 A Non-computable Function
    • 12.5 Complexity of Problems