Computer Science Fundamentals

Computer Science

Artificial Intelligence (AI)

• Definition: AI is a field of computer science that focuses on creating intelligent machines that can perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making.
• Subfields:
  • Machine Learning (ML): a type of AI that enables machines to learn from data without being explicitly programmed.
  • Natural Language Processing (NLP): a subfield of AI that deals with the interaction between computers and humans in natural language.
  • Computer Vision: a subfield of AI that focuses on enabling computers to interpret and understand visual information from the world.
• Applications:
  • Robotics: AI is used to program robots to perform tasks that typically require human intelligence, such as assembly, welding, and material handling.
  • Image Recognition: AI is used in image recognition systems to identify objects, people, and patterns in images.

Database Management

• Definition: Database management refers to the process of designing, implementing, and maintaining databases to store and manage data efficiently.
• Key Concepts:
  • Data Modeling: the process of creating a conceptual representation of data structures and relationships.
  • Data Normalization: the process of organizing data to minimize data redundancy and improve data integrity.
  • Database Query Languages: languages used to manage and retrieve data from databases, such as SQL.
• Database Types:
  • Relational Databases: databases that organize data into one or more tables with rows and columns.
  • NoSQL Databases: databases that do not use the traditional table-based relational model, such as key-value, document, and graph databases.

Software Engineering

• Definition: Software engineering is the application of engineering principles and techniques to the design, development, testing, and maintenance of software systems.
• Key Concepts:
  • Software Development Life Cycle (SDLC): a framework used to plan, design, build, test, and deploy software systems.
  • Requirements Analysis: the process of identifying and documenting software requirements.
  • Design Patterns: reusable solutions to common software design problems.
• Software Development Methodologies:
  • Agile Development: an iterative and incremental approach to software development that focuses on flexibility and customer satisfaction.
  • Waterfall Development: a linear approach to software development that follows a sequential phase-by-phase approach.