Version: 0.6.1

Algorithms and Data Structures

About This Course

• Welcome!
  • What Can You Expect from Me?
  • What Do I Expect from You?
• Course Overview
  • Syllabus
  • Why to Study This?
  • Learning Outcomes
    • Competence
    • Skills
    • Knowledge
• Practicalities
  • Lectures
  • Lab Sessions
• Examination
• Additional Resources
  • Textbooks
  • Online Courses
  • Programming Platforms

Modules

• Foundations
  • Contents
    • 1. Computations
      • 1.1. Computation
      • 1.2. Algorithms
      • 1.3. Data Structures
      • 1.4. How to Describe an Algorithm?
      • 1.5. Conclusions
    • 2. Computer
      • 2.1. Random Access Machines
      • 2.2. Programming Languages
      • 2.3. Conclusion
    • 3. Correctness
      • 3.1. Functional Correctness?
      • 3.2. Formal Proofs
      • 3.3. Testing
      • 3.4. Conclusion
    • 4. Efficiency
      • 4.1. Running Example
      • 4.2. Benchmarking Performance
      • 4.3. Computational Complexity
      • 4.4. Conclusion
    • 5. Algorithm Analysis
      • 5.1. Modeling Algorithm Efficiency
      • 5.2. Best, Worst, and Average Cases
      • 5.3. Conclusions
    • 6. The Big-O Notation
      • 6.1. Comparing Efficiencies
      • 6.2. Asymptotic Analysis
      • 6.3. Orders of Growth
      • 6.4. Conclusions

Lab Sessions

• Setup
• Foundations
  • Java Refresher
  • Random Access Machines
  • Correctness
  • Cost Models
  • Efficiency

Code Examples

• Edge List Pattern in Ruby
• Adjacency List in JavaScript
• Adjacency Matrix in C

Recaps

• Math Recap
  • Logic
  • Sets
  • Sequences & Tuples
  • Functions
  • Probabilities
  • Calculus
    • Exponents
    • Logarithms
    • Summations
    • Products
    • Factorial
  • Combinatorics
    • Permutations
    • Combinations

Indices and Tables

• Index

• Module Index

• Search Page