1. Computational Thinking and the Hour of Code
- Computational Thinking https://giiestemb.wordpress.com/computational-thinking
- Hour of Code https://giiestemb.wordpress.com/hourofcode/
Embedded Files
Resources
- Logo (programming language) https://en.wikipedia.org/wiki/Logo_(programming_language)
- Logo Interpreter https://www.calormen.com/jslogo/
- Turtle Academy https://turtleacademy.com/
- Fortran https://en.wikipedia.org/wiki/Fortran
- Lisp (programming language) https://en.wikipedia.org/wiki/Lisp_(programming_language)
- Grace Hopper - COBOL
- Java (programming language) https://en.wikipedia.org/wiki/Java_(programming_language)
- Python (programming language) https://en.wikipedia.org/wiki/Python_(programming_language)
- JavaScript https://en.wikipedia.org/wiki/JavaScript
- https://www.pythonanywhere.com/
- https://colab.research.google.com
- Lab1
2. Some Examples of Algorithms Applications and Hard Algorithmic Problems
- Graph Algorithms
- Hard Algorithmic Problems
- TSP - Orion UPS
- Graph Isomorphism
- SAT
- NP (complexity) https://en.wikipedia.org/wiki/NP_(complexity)
- NP-hardness https://en.wikipedia.org/wiki/NP-hardness
- NP-complete problems https://en.wikipedia.org/wiki/NP-completeness
- P versus NP https://en.wikipedia.org/wiki/P_versus_NP_problem
- Stephan Ceroi´s lectures (in Spanish), ceroi@lirmm.fr in Calculability and Complexity
- String Processing Algorithms
- Information Retrieval
- Personalized Medicine
- 10 most influential algorithms in science and engineering of the 20th century
Resources
- Udacity CS215 Intro to Algorithms
- Coursera Algorithms on Graphs
- OM in the News: At UPS, the Algorithm is the Truck Driver Feb. 24, 2015 tags: algorithms, ORION, routing, scheduling, travelling salesman, UPS by Barry Render OM Blog
- At UPS, the Algorithm Is the Driver, Steven Rosenbush and Laura Stevens, WSJ, Feb. 16, 2015 8:28 p.m. (local)
- A Quasipolynomial Time Algorithm for Graph Isomorphism: The Details Math ∩ Programming jeremykun.com
- The international SAT Competitions web page https://www.satcompetition.org/
- Prizes Aside, the P-NP Puzzler Has Consequences nytimes.com
- Coursera Algorithms on Strings
- Vishal Sikka: The beauty and power of algorithms TED Talk
- Pratik Shah: How AI is making it easier to diagnose disease TED Talk
- Chinese scientists are creating CRISPR babies Antonio Regalado November 25, 2018 technologyreview.com
- The Algorithm for Precision Medicine youtube.com
- Top Ten Algorithms algorithms having "the greatest influence on the development and practice of science and engineering in the 20th century" nominated by the journal Computing in Science and Engineering February 2000
3. What is an algorithm?
- What is an algorithm?
- Semantic analysis
- Correctness
- Complexity
- Time complexity
- Elementary operation
- Principle of invariance
4. Competitive Programming
Ivan Castellanos
- Grupo de Maratones UN: www.facebook.com/groups/maratonesunbogota/
- IEEEXtreme: Slides talk J.S. Dussan
- codeforces.com
- icpc.baylor.edu
- https://www.hackerearth.com/
- https://www.hackerrank.com/
- UVa Online Judge
- icpc.baylor.edu/compete/problems
- CS 97SI: Introduction to Programming Contests - Jaehyun Park - Stanford University
- CS3233 Competitive Programming - old teaching materials - Steven Halim - NUS
- Competitive Programmer's Core Skills Coursera - Saint Petersburg State University
- Competitive Programmer's Handbook PDF - Code Submission Evaluation System Finland - CSES
- Common mistakes to be avoided in Competitive Programming in C++ | Beginners - Geeksforgeeks
- Python - Most frequent problem for beginners (on Hackerearth) - Rishikesh Agrawani - Linkedin
5. String algorithms and bioinformatics
Luis Fernando Niño
Resources
6. Brute force and Incremental Paradigm
- Brute force
- Incremental Paradigm
- Insertion sort
- Incremental Recurrences
- Bubble sort
7. Divide and Conquer I - Merge Sort
- Divide and Conquer Paradigm
- Merge Sort
- Time Complexity Merge Sort
8. Growth of Functions
- Asymptotic notation
- Common functions
Resources
- CLRS I.3
- DVP 0.3
- grofun.pdf
- grofun.zip
- MIT Introduction-to-algorithms 2005
- Lab 4
9. Divide and Conquer Paradigm II
- Other Examples of D-C
- Chip Testing Problem
- Binary Search
- Convex Hull
- Towers of Hanoi
- Alternative Methods to Solve D-C Recurrences
- Characteristic equation method
- Substitution method
- Master method
- Z transform
Resources
- CLRS I.4
- DVP 2
- divcon2.pdf
- divcon2.zip
- DISI Applets
- Binary and Linear Search Visualization
- Divide and Conquer - Convex Hull
- https://visualgo.net/en/convexhull
- Divide and Conquer, Merger Sort y complejidad de recurrencias Programacion Competetiva UNAL
- MIT Introduction-to-algorithms 2005
- Towers of Hanoi Animation
- Videos
- Algorithms UN 6.1 Divide and Conquer Paradigm II - Youtube
- Algorithms UN 6.2 Divide and Conquer Paradigm II - Youtube
- Algorithms UN 6.3 Divide and Conquer Paradigm II - Youtube
- Algorithms UN 6.4 Divide and Conquer Paradigm II - Youtube
- Algorithms UN 6.5 Divide and Conquer Paradigm II - Youtube
- Algorithms UN 6.6 Divide and Conquer Paradigm II - Youtube
10. Trading Algorithms
Resources
- Quantopian
- Quantopian wikiepdia
- Hello World Example
- Cross-sectional Equity Template Example
- Project in algorithmic trading 30%
- Build three algorithms as modifications of the Cross-sectional Equity Template Example to include minimum 6 variables(the example uses three) and sing a weighted sum for the combined_factor (the example uses just adds the three variables which is equivalent to use weights of 1). Perform backtestings for your three algorithms for the past 1 and 2 years.
- Information about other data variables that can be used
- You should write a report inOverleaf explaining what variables did you include and why, a brief explanation of the variables included, how did you find the weights backtesting results. The codes should be published in your GitHub account. If you do the alphalens analysis you will have and 2 % extra credit for each algorithm. the analysis should be also published in your GitHub account. Send links to the Overlaf report and to the GitHub codes and notebooks in the corresponding assignment in Moodle.
- If any of your codes is accepted in the contest you will have a 10 extra credit for each
11. Dynamic Programming
Resources
- CLRS IV.15
- DVP 6
- An introduction to the theory of dynamic programming - R, Bellman - RAND -1954 - Dtic.Mil - pdf
- DP Grupo de Maratones UN
- Lecture 15: Dynamic Programming, Longest Common Subsequence MIT Introduction to Algorithms (SMA 5503 ) Fall 2005
- Lecture 10 Dynamic Programming Ackerman FSU
- Competitive Programmer's Handbook PDF - Chapter 7 Dynamic Programming
- IPython notebook: timeitexmaples
12. Efficient Data Structures - Heap Sort
- Binary heaps
- Heap sort
- Priority queues
Resources
- CLRS II.6
- heapsort.pdf
- heapsort.zip
- VisuAlgo - https://visualgo.net/en/heap
- IPython notebook: montículos
- Lecture 4: Heaps and Heap Sort MIT Introduction to Algorithms( 6.006) Fall 2011
- Udacity CS 215 Lesson 4: It’s Who You Know Keeping track of your best friends using heaps
- DISI HeapSort
- Sorting Comparison Demos
13. Randomization - Select and Quick Sort
- Medians and Order Statistics
- Randomized Select
- Deterministic Select
- Quicksort
- Randomized Quicksort
Resources
- CLRS II.7
- DVP 2.4
- selectquicksort.pdf
- selectquicksort.zip
- https://visualgo.net/bn/sorting
- DISI Quicksort
- Lecture 6: Order Statistics, Median MIT Introduction to Algorithms (SMA 5503 ) Fall 2005
- Median - Wikipedia
- Percentile - Wikipedia
- Quantile - Wikipedia
- Order Statistic -- from Wolfram MathWorld
- Computer Generation of Statistical Distributions
- Lecture 4: Quicksort, Randomized Algorithms MIT Introduction to Algorithms (SMA 5503 ) Fall 2005
- Quicksort form interactivepython.org
- IPython notebook:quicksort from interactivepython.org
- IPython notebook: randomquicksort distr comps(tiempo)
- IPython notebook: quicksort two finger comp distrib (tiempo)
- DISI Applets
- Sorting Comparison Demos
- Distributional Convergence for the Number of Symbol Comparisons Used by QuickSort from JA Fill, Johns Hopkings U.
- Distributional Convergence for the Number of Symbol Comparisons Used by QuickSelect.from JA Fill, Johns Hopkings U.
14. Input Tuning - Sorting in Linear Time
- Lower bound for sorting
- Counting sort
- Radix sort
- Bucket sort
Resources
- CLRS II.8
- DVP Pg 63
- sortinginlineartime.pdf
- sortinginlineartime.zip
- https://visualgo.net/bn/sorting
- Lecture 5: Linear-time Sorting: Lower Bounds, Counting Sort, Radix Sort MIT Introduction to Algorithms (SMA 5503) Fall 2005
15. Graph Algorithms
Resources
- IPython notebook: búsquedas
- IPython notebook: Dijksitra
- IPython notebook: Djkstra_eppstein
- IPython notebook: BellmanFord
- IPython notebook: FloydWarshall
- DISI decompositions_of_graphs.rar
- DISI ch04-paths-in-graphs.ppt
- Lecture 17: Shortest Paths I: Properties, Dijkstra's Algorithm, Breadth-first Search ,
- Lecture 18: Shortest Paths II: Bellman-Ford, Linear Programming, Difference Constraints and
- Lecture 19: Shortest Paths III: All-pairs Shortest Paths, Matrix Multiplication, Floyd-Warshall, Johnson MIT Introduction to Algorithms (SMA 5503 ) Fall 2005
- CS3233 Competitive Programming - old teaching materials - Steven Halim, NUS, week05_graph_1.pdf
- Udacity CS 215 Lesson 5: Strong and Weak Bonds Working with social networks with edge weights
16 Greedy algorithms
Resources
- CLRS IV.16
- DVP 5
- Lecture 16: Greedy Algorithms, Minimum Spanning Tree MIT Introduction to Algorithms (SMA 5503) Fall 2005
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