What you will learn in Algorithms Specialization Course
- Understand fundamental algorithms and their applications
- Learn problem-solving approaches like divide-and-conquer, dynamic programming, and greedy algorithms
- Analyze algorithm efficiency using Big-O notation
- Explore graph algorithms including shortest paths and spanning trees
- Tackle NP-complete problems and approximation techniques
- Build strong theoretical and practical algorithmic skills
Program Overview
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
⏱️ 1 week
- Learn asymptotic analysis and algorithm efficiency
- Master divide-and-conquer strategies and sorting/searching algorithms
- Explore randomized algorithms for performance optimization
Graph Search, Shortest Paths, and Data Structures
⏱️ 1 week
- Use BFS and DFS for graph exploration
- Study Dijkstra’s and Bellman-Ford algorithms
- Understand heaps, stacks, queues, and balanced trees
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
⏱️1 week
- Solve optimization problems using greedy strategies
- Learn Kruskal’s and Prim’s algorithms
- Implement dynamic programming for complex problems
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
⏱️ 1 week
- Delve into advanced shortest path algorithms
- Grasp the concept of NP-completeness
- Explore practical approaches to intractable problems
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Job Outlook
Highly relevant for roles in software engineering, data science, and tech research
Strengthens core skills required for technical interviews
In demand by top tech firms for algorithm-heavy roles
Lays a solid foundation for advanced CS fields like machine learning and AI
Certification from Stanford boosts professional credibility
Equips learners to contribute to efficient, scalable systems design
Specification: Algorithms Specialization
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