Coordinates  TR, 1011:20am, GLSN 200 [Registrar] [Canvas] 
Instructor 
Liang Huang

TAs  He Zhang (zhangh7@) and Yilin Yang (yangyil@) 
Office hours  Liang: T/Th, 11:2511:55am (KEC 2069); TAs: M/T/Th/F, 45pm (KEC Atrium). 
Textbooks  [CLRS] Introduction to Algorithms, 3rd or 2nd edi. (default reference).
[KT] Kleinberg and Tardos, Algorithm Design (DP chapter online, all slides online) [DPV] Dasgupta, Papadimitriou, and Vazirani (DPV). Algorithms (full text online via berkeley) [E] Jeff Erickson. Algorithms, Etc. (full text online) How to Think Like a Computer Scientist: Learning Python (full text online) 
Grading (tentative)  midterm: 20%, final: 25%, three quizzes: 7x3=21%; weekly homework: 3x10=30%, class participation: 4%. any complete HW submission automatically gets 2%. the other 1% is based on blackbox testing of the specified coding problem. no late submission is accepted. Grading Curve: A/A: 4045%, B+/B/B: 4550%, the rest is C+/C/C (very rare). 
Intended Audience 

Other Policies 
For technical questions, come to office hours.
Otherwise you can raise a question on Canvas. (answering other people's questions correctly will be rewarded for class participation). For grading questions, come to office hours. Do not email us unless you have a personal issue. 
Week  Topics  Homework  Quiz/Exam 
1  (Tue) Admin Python Tutorial quicksort, BST, quickselect (Thu) mergesort, twopointers, stable sort  HW1 (qselect, qsort>bst)  
2  (Tue)
dividenconquer: number of inversions longest path in binary tree brief discussions of HW1 (Thu) k numbers closest to input query, unsorted and sorted quiz1 and discussions x+y=z  HW2 (msort, inv, longest)  Thu: Quiz 1 (covers HW1) 
To prepare for coding interviews, you have to practice on some of the above (say, solving at least 20 problems on codeforces, with at least two from each topic). To prepare for ACM/ICPC, you have to practice a lot (solving at least 100 problems on zoj/poj).
For another MS/MEnglevel algorithms class I taught before (at USC), see here (with lots of details on analysis of complexity).