Design and Analysis, Part 1″ is an in-depth exploration of fundamental algorithms and algorithmic techniques. Taught by Professor Tim Roughgarden, this course focuses on the basics of algorithms, including their design, analysis, and optimization. It teaches students to approach complex computational problems systematically by employing key techniques like divide-and-conquer, dynamic programming, and greedy algorithms.
Duration:
6 weeks or more to complete, with an estimated commitment of 5-7 hours per week.
Platform:
Available through Coursera as part of Stanford’s online offerings.
Key Topics Covered:
- Asymptotic analysis (Big O notation)
- Divide-and-conquer algorithms (MergeSort, QuickSort)
- Graph search algorithms (Breadth-First Search, Depth-First Search)
- Greedy algorithms
- Dynamic programming
- Data structures (heaps, hash tables, balanced binary search trees)
Who Is It For:
This course is tailored for computer science students, software engineers, and professionals aiming to enhance their algorithmic problem-solving abilities.
Learning Outcomes: By the end of the course, students will be able to:
- Design efficient algorithms to solve complex computational problems.
- Analyze algorithms for efficiency and correctness using mathematical techniques.
- Apply divide-and-conquer, greedy, and dynamic programming strategies to practical problems.
Prerequisites:
Basic knowledge of programming and data structures. Familiarity with discrete mathematics and proof techniques (e.g., proof by induction) is recommended.
Visit the Official Course Page:
For more details and to enroll, visit the official course page.