Course Overview
This fast-paced ISACA: Data Science Fundamentals course combines classroom instruction with performance-based learning. This fusion of theoretical learning and practical application creates a genuinely distinctive and dynamic learning experience that develops and reinforces the crucial skills needed to carry out many of the technical tasks required by the IT work environment.
Audience Profile
This course is ideal for:
- If you are willing to pursue a career in information technology or cybersecurity or building your current baseline skills, through a world-renowned cybersecurity platform, this course is ideal for you.
Learning Objectives
- Explaining data characteristic, data types, uses, and structures of data
- Summarizing common statistical methods and how to gauge KPIs
- Defining different data management systems
- Explaining the basic concepts, and procedures for data governance
- Explaining the methods for protecting data Identify the phases of the data collection & data analysis process
- Describing the complete data science process
Content Outline
1- Data Characteristics: Basic Concepts
- Defining the terms and concepts of data science.
- Describing the relationship between data science and statistics.
- Describe the classifications and characteristics of data.
Learning Objectives (2)
- Explaining the different types of data structures, flows and diagrams.
Learning Objectives (3)
- Explaining the different types of data structures, flows and diagrams.
Learning Objectives (4)
- Using statistical analysis to gather populations and samples.
- Distinguishing among sampling techniques.
Learning Objectives (5)
- Distinguishing among different data storage and management systems.
- Describe the benefits of using automated processes to manage data.
Learning Objectives (6)
- Identify elements within a database management system.
- Explain the use of data in online and cloud-based applications.
Learning Objectives (7)
- Explain legal, regulatory and ethical considerations regarding use of data.
Learning Objectives (8)
- Explain legal, regulatory and ethical considerations regarding use of data.
- Detail data governance roles and responsibilities.
Learning Objectives (9)
- Distinguish among data obfuscation, tokenization and encryption.
Learning Objectives (10)
- Identify open and cross-industry standards used to process data.
- Describe techniques used to collect data.
Learning Objectives (11)
- Explain activities performed to prepare data for analysis, categorization and modelling.
Learning Objectives (12)
- Identify methods to uncover relationships among data.
- Identify tools used to build, model and analyse data.
- Describe concepts related to business analytics.
Learning Objectives (13)
- Distinguish among types of machine learning algorithms.
Learning Objectives (14)
- Distinguish among types of visualization and reporting tools.
FAQs
Data science is the study of how to use statistics and machine learning to analyse raw data in order to make inferences about that data.
It takes several factors and parts in order to manage data science projects. This article will provide you with the five key elements: purpose, people, processes, platforms and programmability [1], and how you can benefit from these in your projects.
Statistics, Visualization, Deep Learning, Machine Learning are important Data Science concepts
A: To attend the training session you should have an operational Desktops or Laptops with required specification along with good internet connection to access the labs.
A: We would always recommend you to attend the live session to practice & clarify the doubts instantly and get more value from your investment. However, if due to some contingency if you have to skip the class Radiant Techlearning would help you with the recorded session of that particular day. However, those recorded sessions are not meant only for personal consumption and NOT for distribution or any commercial use.
A: Radiant Techlearning has a data center containing the Virtual Training environment for the purpose of participant’s hand-on-practice.
Participants can easily access these labs over Cloud with the help of remote desktop connection.
Radiant virtual labs provides you the flexibility to learn from anywhere in the world and in any time zone.
A: The learners will be enthralled as we engage them the real world and industry Oriented projects during the training program. These projects will improve your skills and knowledge and you will gain better experience. These real time projects, they will help you a lot in your future tasks and assignments.