Introduction to Computer Science

Complete syllabus

Every chapter and lesson

1. 01

   Chapter 1 · 3 lessons

   Computational Thinking

   1. 1.1

      Algorithms & what CS is

      8 min · Quick check

      Lesson goal: By the end you can define algorithms and explain the fundamentals of computer science.

      • Understand the definition of an algorithm.
      • Identify the components of computer science.
      • Explain the importance of algorithms in problem-solving.
   2. 1.2

      Decomposition & pseudocode

      9 min · Quick check

      Lesson goal: By the end you can apply decomposition and pseudocode to break down problems.

      • Define decomposition and its role in problem-solving.
      • Understand what pseudocode is and how it is used.
      • Practice writing pseudocode for simple algorithms.
   3. 1.3

      How computers represent data

      8 min · Quick check

      Lesson goal: By the end you can describe how computers represent data using binary.

      • Define data representation in computing.
      • Explain the concept of binary and its significance.
      • Identify different types of data that can be represented in a computer.
2. 02

   Chapter 2 · 3 lessons

   Programming Foundations

   1. 2.1

      Variables, types & expressions

      9 min · Quick check

      Lesson goal: By the end you can understand and utilize variables, data types, and expressions in programming.

      • Define what a variable is and its purpose in programming.
      • Identify different data types such as integers, floats, strings, and booleans.
      • Explain how expressions are formed using variables and operators.
   2. 2.2

      Conditionals & boolean logic

      9 min · Quick check

      Lesson goal: By the end you can apply conditionals and boolean logic to control the flow of a program.

      • Define conditionals and their role in decision-making in programming.
      • Explain boolean logic and the use of operators like AND, OR, and NOT.
      • Illustrate how to write if-else statements to execute different code paths.
   3. 2.3

      Loops & iteration

      8 min · Quick check

      Lesson goal: By the end you can implement loops and iteration to perform repetitive tasks in programming.

      • Define what loops are and their importance in programming.
      • Differentiate between for loops and while loops.
      • Demonstrate how to use loops to iterate over data structures.
3. 03

   Chapter 3 · 3 lessons

   Structuring Code

   1. 3.1

      Functions & decomposition

      9 min · Quick check

      Lesson goal: By the end you can explain the concept of functions and how decomposition helps in structuring code.

      • Define functions and their purpose in programming.
      • Explain the process of decomposition in breaking down problems.
      • Discuss the benefits of using functions for code organization.
   2. 3.2

      Parameters & scope

      8 min · Quick check

      Lesson goal: By the end you can describe parameters and scope in the context of functions.

      • Define parameters and their role in functions.
      • Explain the concept of scope and its importance in programming.
      • Differentiate between local and global variables.
   3. 3.3

      Debugging & testing

      8 min · Quick check

      Lesson goal: By the end you can apply debugging and testing techniques to identify and fix errors in code.

      • Define debugging and its significance in software development.
      • Describe various testing methods to ensure code quality.
      • Discuss common debugging strategies and tools.
4. 04

   Chapter 4 · 3 lessons

   Data Structures

   1. 4.1

      Arrays & lists

      9 min · Quick check

      Lesson goal: By the end you can explain the concepts of arrays and lists and their applications in programming.

      • Define arrays and lists and their differences.
      • Identify the structure and characteristics of arrays and lists.
      • Explain how to access and manipulate elements in arrays and lists.
      • Discuss the advantages and disadvantages of using arrays versus lists.
   2. 4.2

      Dictionaries & sets

      8 min · Quick check

      Lesson goal: By the end you can describe dictionaries and sets and their roles in data management.

      • Define dictionaries and sets and their unique properties.
      • Explain how to create and access elements in dictionaries and sets.
      • Discuss the use cases for dictionaries and sets in programming.
      • Identify the differences between mutable and immutable data types.
   3. 4.3

      Strings & text processing

      8 min · Quick check

      Lesson goal: By the end you can understand strings and text processing techniques in programming.

      • Define strings and their importance in programming.
      • Explain common string operations and methods.
      • Discuss text processing techniques and their applications.
      • Identify challenges in text processing and how to address them.
5. 05

   Chapter 5 · 3 lessons

   Algorithms

   1. 5.1

      Searching

      9 min · Quick check

      Lesson goal: By the end you can define searching algorithms and explain their importance in computer science.

      • Understand the definition of searching algorithms.
      • Learn about different types of searching algorithms, such as linear and binary search.
      • Explore the applications of searching algorithms in real-world scenarios.
   2. 5.2

      Sorting

      8 min · Quick check

      Lesson goal: By the end you can define sorting algorithms and describe their significance in data organization.

      • Understand the definition of sorting algorithms.
      • Learn about various sorting algorithms, including bubble sort and quicksort.
      • Examine the applications of sorting algorithms in data management.
   3. 5.3

      Big-O & efficiency

      9 min · Quick check

      Lesson goal: By the end you can explain Big-O notation and its role in analyzing algorithm efficiency.

      • Define Big-O notation and its importance in algorithm analysis.
      • Learn how to evaluate the efficiency of algorithms using Big-O notation.
      • Explore examples of different algorithms and their Big-O classifications.
6. 06

   Chapter 6 · 3 lessons

   Big Ideas in Computing

   1. 6.1

      Recursion

      9 min · Quick check

      Lesson goal: By the end you can explain the concept of recursion and its applications in programming.

      • Define recursion as a method where the solution to a problem depends on solutions to smaller instances of the same problem.
      • Identify base cases that terminate the recursive calls.
      • Discuss examples of recursive functions, such as factorial calculation and Fibonacci sequence.
      • Explain the importance of stack memory in recursion.
   2. 6.2

      How the internet works

      8 min · Quick check

      Lesson goal: By the end you can describe how the internet functions and its key components.

      • Define the internet as a global network of interconnected computers that communicate using standardized protocols.
      • Explain the role of Internet Protocol (IP) addresses in identifying devices on the network.
      • Discuss the function of servers and clients in the context of web services.
      • Identify the importance of routers and switches in directing data traffic.
   3. 6.3

      Data, security & impact

      8 min · Quick check

      Lesson goal: By the end you can analyze the relationship between data, security, and its societal impact.

      • Define data as information processed or stored by a computer.
      • Discuss the significance of data security in protecting sensitive information.
      • Identify potential impacts of data breaches on individuals and organizations.
      • Explore ethical considerations surrounding data collection and usage.