Informatics II

Syllabus

1. Basic concepts in informatics Content: Definitions of data, information, knowledge, and skills. Classification of data types and their use in real-world scenarios. Activities: Classification exercises, discussion on types of data and their importance. Outcome: Short essay on data and information in the enterprise environment. 2. Encoding and encryption; numeral systems Content: Definitions and comparison of encoding vs encryption. Introduction to numeral systems: binary, decimal, hexadecimal. Activities: Number conversions, basic encoding techniques, Caesar cipher example. Outcome: Presentation on data security and encoding. 3. Binary representation of data and basic units Content: Representation of numeric, textual, graphic, and multimedia data in binary system. Bit, byte, word. Activities: ASCII/UTF-8 encoding exercises, file size calculations. Outcome: Solved worksheet with binary conversions. 4. Introduction to software – classifications and types Content: System, application, and utility software. Licensing models: open-source vs proprietary. Activities: Compare software tools used in business. Outcome: Summary report on software categories. 5. Operating systems and peripheral communication Content: Role of OS, device drivers, resource management. Activities: Practice in configuring devices and driver installation. Outcome: Configuration report. 6. Application software classification Content: General-purpose vs specialized application software in industries. Activities: Analysis of tools used in different sectors. Outcome: Software catalog categorized by sector. 7. Office software Content: Word processing, spreadsheets, presentations. Activities: Create documents, financial spreadsheets, and business slides. Outcome: Set of business documents using MS Office or LibreOffice. 8. Specialized software for various domains Content: Software used in education, engineering, construction, healthcare, etc. Activities: Case studies and tool comparison. Outcome: Seminar paper analyzing software usage in one domain. 9. Network-related software tools Content: Tools for file sharing, drive mapping, remote access. Activities: Configure and test local network sharing. Outcome: Documentation of configuration and tools used. 10. Communication tools and platforms Content: Email, chats, video conferencing, remote desktop. Activities: Simulated team communication using MS Teams, Zoom, or Slack. Outcome: Communication protocol and tools evaluation. 11. Collaborative teamwork tools Content: Cloud collaboration (Google Docs, OneDrive), version tracking. Activities: Create a shared team document or presentation. Outcome: Team-created document with version history. 12. Shared computing resources – grid and cloud Content: Cloud services (IaaS, PaaS, SaaS), distributed computing. Activities: Use of a free cloud service tier (Google Cloud/Azure). Outcome: Poster or short report on benefits and challenges of cloud solutions. 13. Introduction to cybersecurity and digital law Content: Computer viruses, malware types, basics of IT law. Activities: Analyze real-world cybersecurity case. Outcome: Essay on data protection and digital rights. Programming Lab 1. Introduction to R language Basic R syntax, RStudio environment setup, interactive execution. 2. Creating and managing R objects Scalars, vectors, lists, matrices, and data frames. 3. Data types and differences Numeric, logical, character, and factor types. 4. Operators and expressions Arithmetic, relational, logical, and special operators. 5. Built-in functions Use of basic functions such as sum(), mean(), length(), etc. 6. Data structures in R Manipulating data frames, filtering, and subsetting. 7. Basic data processing Sorting, filtering, grouping, and transforming data. 8. Working with external files Import/export of CSV, Excel, and text files. 9. Control structures Conditional statements (if, else), loops (for, while). 10. The apply family of functions lapply(), sapply(), tapply(), vapply() – when and how to use them. 11. Creating custom functions Function definition, arguments, and return values. 12. Graphing in R Basic plots: histograms, box plots, scatter plots. 13. Using external libraries Working with tidyverse, dplyr, ggplot2, and readr.