Algorithmic Toolbox Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This course provides a comprehensive introduction to algorithmic techniques and computational problem-solving, designed for learners with basic programming knowledge. The curriculum spans six modules, each focusing on a core algorithmic paradigm, blending theory with hands-on programming assignments. With approximately 5 hours per module, learners will complete the course in about 30 hours. The flexible structure makes it ideal for working professionals aiming to strengthen their algorithmic thinking and prepare for technical interviews.
Module 1: Programming Challenges
Estimated time: 5 hours
- Introduction to algorithmic problem-solving
- Setting up the programming environment
- Basic code debugging and testing
- Solving simple computational problems
Module 2: Algorithmic Warm-up
Estimated time: 5 hours
- Computing Fibonacci numbers efficiently
- Finding greatest common divisors (GCD)
- Calculating least common multiples (LCM)
- Understanding algorithm efficiency
Module 3: Greedy Algorithms
Estimated time: 5 hours
- Principles of greedy strategies
- Solving the coin change problem
- Task scheduling optimization
- Greedy choice and optimal substructure
Module 4: Divide and Conquer
Estimated time: 5 hours
- Binary search implementation
- Quicksort and its analysis
- Counting inversions in arrays
- Recurrence relations and complexity
Module 5: Dynamic Programming 1
Estimated time: 5 hours
- Introduction to dynamic programming
- Computing edit distance between strings
- Finding longest common subsequence
- Overlapping subproblems and memoization
Module 6: Dynamic Programming 2
Estimated time: 5 hours
- Knapsack problem variations
- Optimal solution using dynamic programming
- Evaluating arithmetic expressions
- Advanced DP problem-solving techniques
Prerequisites
- Basic programming experience in any language
- Familiarity with fundamental data structures (arrays, lists)
- Elementary mathematical reasoning skills
What You'll Be Able to Do After
- Master fundamental algorithmic techniques
- Design and implement efficient algorithms
- Solve complex computational problems
- Tackle algorithmic challenges in technical interviews
- Enhance problem-solving abilities through hands-on practice