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자막: 영어, 스페인어

배울 내용

  • Essential algorithmic techniques

  • Design efficient algorithms

  • Practice solving algorithmic interview problems

  • Implement efficient and reliable solutions

귀하가 습득할 기술

Dynamic ProgrammingDebuggingSoftware TestingAlgorithmsComputer Programming

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가 이 강좌를 수료한 후 새로운 커리어를 시작함

36%

가 이 강좌를 통해 확실한 경력상 이점을 얻음

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가 급여 인상 또는 승진 성취
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다음 특화 과정의 6개 강좌 중 1번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
중급 단계
완료하는 데 약 37시간 필요
영어
자막: 영어, 스페인어

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강의 계획 - 이 강좌에서 배울 내용

콘텐츠 평가Thumbs Up92%(102,210개의 평가)Info
1

1

완료하는 데 5시간 필요

Programming Challenges

완료하는 데 5시간 필요
6개 동영상 (총 48분), 7 개의 읽기 자료, 3 개의 테스트
6개의 동영상
Solving the Sum of Two Digits Programming Challenge (screencast)6m
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13m
Stress Test - Implementation8m
Stress Test - Find the Test and Debug7m
Stress Test - More Testing, Submit and Pass!8m
7개의 읽기 자료
Companion MOOCBook10m
What background knowledge is necessary?10m
Optional Videos and Screencasts10m
Alternative testing guide in Python10m
Maximum Pairwise Product Programming Challenge10m
Using PyCharm to solve programming challenges10m
Acknowledgements2m
1개 연습문제
Solving Programming Challenges20m
2

2

완료하는 데 5시간 필요

Algorithmic Warm-up

완료하는 데 5시간 필요
12개 동영상 (총 77분), 3 개의 읽기 자료, 4 개의 테스트
12개의 동영상
Coming Up3m
Problem Overview3m
Naive Algorithm5m
Efficient Algorithm3m
Problem Overview and Naive Algorithm4m
Efficient Algorithm5m
Computing Runtimes10m
Asymptotic Notation6m
Big-O Notation6m
Using Big-O10m
Course Overview10m
3개의 읽기 자료
Resources2m
Resources2m
Resources2m
3개 연습문제
Logarithms10m
Big-O10m
Growth rate10m
3

3

완료하는 데 7시간 필요

Greedy Algorithms

완료하는 데 7시간 필요
10개 동영상 (총 56분), 1 개의 읽기 자료, 8 개의 테스트
10개의 동영상
Car Fueling7m
Car Fueling - Implementation and Analysis9m
Main Ingredients of Greedy Algorithms2m
Celebration Party Problem6m
Efficient Algorithm for Grouping Children5m
Analysis and Implementation of the Efficient Algorithm5m
Long Hike6m
Fractional Knapsack - Implementation, Analysis and Optimization6m
Review of Greedy Algorithms2m
1개의 읽기 자료
Resources2m
2개 연습문제
Greedy Algorithms10m
Fractional Knapsack10m
4

4

완료하는 데 8시간 필요

Divide-and-Conquer

완료하는 데 8시간 필요
20개 동영상 (총 157분), 5 개의 읽기 자료, 9 개의 테스트
20개의 동영상
Linear Search7m
Binary Search7m
Binary Search Runtime8m
Problem Overview and Naïve Solution6m
Naïve Divide and Conquer Algorithm7m
Faster Divide and Conquer Algorithm6m
What is the Master Theorem?4m
Proof of the Master Theorem9m
Problem Overview2m
Selection Sort8m
Merge Sort10m
Lower Bound for Comparison Based Sorting12m
Non-Comparison Based Sorting Algorithms7m
Overview2m
Algorithm9m
Random Pivot13m
Running Time Analysis (optional)15m
Equal Elements6m
Final Remarks8m
5개의 읽기 자료
Resources10m
Resources5m
Resources10m
Resources5m
Resources10m
5개 연습문제
Linear Search and Binary Search10m
Polynomial Multiplication15m
Master Theorem10m
Sorting15m
Quick Sort15m

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데이터 구조 및 알고리즘 특화 과정 정보

This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice. No other online course in Algorithms even comes close to offering you a wealth of programming challenges that you may face at your next job interview. To prepare you, we invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs. Sorry, we do not believe in multiple choice questions when it comes to learning algorithms...or anything else in computer science! For each algorithm you develop and implement, we designed multiple tests to check its correctness and running time — you will have to debug your programs without even knowing what these tests are! It may sound difficult, but we believe it is the only way to truly understand how the algorithms work and to master the art of programming. The specialization contains two real-world projects: Big Networks and Genome Assembly. You will analyze both road networks and social networks and will learn how to compute the shortest route between New York and San Francisco (1000 times faster than the standard shortest path algorithms!) Afterwards, you will learn how to assemble genomes from millions of short fragments of DNA and how assembly algorithms fuel recent developments in personalized medicine....
데이터 구조 및 알고리즘

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