ISACA Certifications

DSFC : Data Science Fundamentals Certificate

Course Duration

4 Days

Delivery

ILT/VILT

Overview

Overview Course Curriculum Training Schedule Exam & Certification FAQs

This course introduces you to data science, a growing and rapidly changing field that is becoming increasingly vital to business survival, job stability, and national security. Data science demands skilled professionals who possess the knowledge, skills, and ability to address the evolving threat landscape.

What You'll Learn

Data Characteristics: Basic Concepts
Use of Data in Information Systems
Data Structures
Statistical Analysis
Types of Databases
Data Management
Governance
Data Governance Roles and Responsibilities
Access and Protection
Data Discovery and Collection
Data Classification
Data Processing Concepts
Data Processing with Machine Learning
Communication of Results
Practice Labs

Who Should Attend

The Data Science Fundamentals Certificate is intended for:

A wide-range of individuals, including:

Those new to IT, students, recent graduates and career changers.
Audit, risk, security and governance professionals looking to gain base-line IT knowledge and skills.
Current IT Professionals looking to reskill or upskill to broaden their IT knowledge and skills or keep up-to-date

Prerequisites

There are no prerequisites required to attend this course.

Learning Journey

Coming Soon...

Module 1: Data Characteristics: Basic Concepts

Learning Objectives

Define the terms and concepts of data science.
Describe the relationship between data science and statistics.
Describe the classifications and characteristics of data.

Topics

What Is Data Science?
Defining Big Data
The Evolution of Big Data
What Is Data?
Raw Data vs. Contextualized Data
Comprehensive version
Difference Between Data Statistics and Analytics
Data Types
ASCII and Unicode

Module 2: Use of Data in Information Systems

Learning Objectives

Explain the different types of data structures, flows and diagrams.

Topics

DIKW Pyramid
Metadata
Data Flows and Data Diagrams
Applicability of Data to Business

Module 3: Data Structures

Learning Objectives

Explain the different types of data structures, flows and diagrams.

Topics

Characteristics of Data Structures
Linear Structures
Tree Structures
Index and Pointer Structures

Module 4: Statistical Analysis

Learning Objectives

Use statistical analysis to gather populations and samples.
Distinguish among sampling techniques.

Topics

Populations and Samples
Statistical Modeling
Key Performance Indicators (KPIs)

Module 5: Types of Databases

Learning Objectives

Distinguish among different data storage and management systems.
Describe the benefits of using automated processes to manage data.

Topics

Introduction
Operational Databases
Relational vs. Non-Relational Databases
Autonomous Databases

Module 6: Data Management

Learning Objectives

Identify elements within a database management system.
Explain the use of data in online and cloud-based applications.

Topics

Common Database Management Systems
Data Lakes
Data Warehouse

Module 7: Governance

Learning Objectives

Explain legal, regulatory and ethical considerations regarding use of data.

Topics

Governance
Data Governance
Legal and Regulatory Compliance

Module 8: Data Governance Roles and Responsibilities

Learning Objectives

Explain legal, regulatory and ethical considerations regarding use of data.
Detail data governance roles and responsibilities.

Topics

Data Ethics
Data Roles and Responsibilities

Module 9: Access and Protection

Learning Objectives

Distinguish among data obfuscation, tokenization and encryption.

Topics

Access and Protection
Data Accessibility and Protection
Managing Permissions
Third-Party and Vendor Access and Management
Data Obfuscation
Tokenization
Encryption

Module 10: Data Discovery and Collection

Learning Objectives

Identify open and cross-industry standards used to process data.
Describe techniques used to collect data.

Topics

Data Discovery and Goal Identification
Requirements and Resources
Formulation of Hypotheses
Data Collection
Database Queries
Data Collection Methods and Techniques

Module 11: Data Classification

Learning Objectives

Explain activities performed to prepare data for analysis, categorization and modeling.

Topics

Data Classification
Data Cleansing
Data Clustering
Data Tagging
Data Governance Tools

Module 12: Data Processing Concepts

Learning Objectives

Identify methods to uncover relationships among data.
Identify tools used to build, model and analyze data.
Describe concepts related to business analytics.

Topics

Introduction
Exploratory Data Analysis
Model Development Tools
Statistical Analysis Tools
Business Analytics

Module 13: Data Processing with Machine Learning

Learning Objectives

Distinguish among types of machine learning algorithms.

Topics

Machine Learning

Module 14: Communication of Results

Learning Objectives

Distinguish among types of visualization and reporting tools.

Topics

Reporting Techniques
Reporting Tools

Module 15: Practice Lab

Creating and Querying Databases with GUI Database Clients
Using GUI Database Clients
Data Cleansing
Metadata
Database Permissions
Data Integrity
File Hashing
Data Management System

Frequently Asked Questions (FAQs)

Why get ISACA certified?

ISACA certifications validate your expertise in critical areas like IT governance, risk management, audit, and cybersecurity.
These globally recognized credentials demonstrate your commitment to professional standards and best practices, enhancing your credibility and opening doors to career advancement.
ISACA-certified professionals are highly sought after by employers worldwide, as they possess the knowledge and skills to navigate the complex landscape of IT governance, risk, and cybersecurity.
What to expect for the examination?

ISACA certification exams are rigorous assessments designed to test your knowledge and understanding of specific domains.
Exams typically consist of multiple-choice questions, and some may include scenario-based questions that assess your ability to apply your knowledge in real-world situations.
Note: Certification requirements and policies may be updated by ISACA from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.
How long is ISACA certification valid for?

ISACA certifications do not expire. However, to maintain your certified status and demonstrate your ongoing commitment to professional development, you must: adhere to the Continuing Professional Education (CPE) policy.
This involves earning and reporting a specific number of CPE hours annually through activities like attending conferences, webinars, training courses, or self-study.
Other requirements include paying an annual maintenance fee as well as complying with the annual CPE audit if selected.
Note: Certification requirements and policies may be updated by ISACA from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.
Why take this course with Trainocate?

Here’s what sets us apart:
- Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 24 countries (and counting!).
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- Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.
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- Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.