Essential Algorithms: A Practical Approach to Computer Algorithms Using Python and C#
(ESS-ALGO.AE1)
/ ISBN: 978-1-64459-270-0
This course includes
Lessons
TestPrep
Lab
Mentoring (Add-on)
Essential Algorithms: A Practical Approach to Computer Algorithms Using Python and C#
Enroll yourself in the Essential Algorithms: A Practical Approach to Computer Algorithms Using Python and C# course and lab to learn algorithms techniques. The course and lab provide expertise over the concepts such as algorithms, linked lists, arrays, stacks and queues, sorting, searching, hash tables, recursion, trees, cryptography, complexity theory, interview puzzles, and more.
Lessons
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21+ Lessons
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168+ Quizzes
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434+ Flashcards
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436+ Glossary of terms
TestPrep
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60+ Pre Assessment Questions
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57+ Post Assessment Questions
Lab
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42+ Performance lab
- Why You Should Study Algorithms
- Algorithm Selection
- Who This Course Is For
- Getting the Most Out of This Course
- How This Course Is Structured
- What You Need to Use This Course
- Conventions
- Approach
- Algorithms and Data Structures
- Pseudocode
- Algorithm Features
- Practical Considerations
- Summary
- Exercises
- Randomizing Data
- Finding Greatest Common Divisors
- Performing Exponentiation
- Working with Prime Numbers
- Performing Numerical Integration
- Finding Zeros
- Gaussian Elimination
- Least Squares Fits
- Summary
- Exercises
- Basic Concepts
- Singly Linked Lists
- Doubly Linked Lists
- Sorted Linked Lists
- Self-Organizing Linked Lists
- Linked-List Algorithms
- Multithreaded Linked Lists
- Linked Lists with Loops
- Summary
- Exercises
- Basic Concepts
- One-Dimensional Arrays
- Nonzero Lower Bounds
- Triangular Arrays
- Sparse Arrays
- Matrices
- Summary
- Exercises
- Stacks
- Queues
- Binomial Heaps
- Summary
- Exercises
- O(N2) Algorithms
- O(N log N) Algorithms
- Sub O(N log N) Algorithms
- Summary
- Exercises
- Linear Search
- Binary Search
- Interpolation Search
- Majority Voting
- Summary
- Exercises
- Hash Table Fundamentals
- Chaining
- Open Addressing
- Summary
- Exercises
- Basic Algorithms
- Factorial
- Fibonacci Numbers
- Rod-Cutting
- Tower of Hanoi
- Graphical Algorithms
- Koch Curves
- Hilbert Curve
- Sierpiński Curve
- Gaskets
- The Skyline Problem
- Backtracking Algorithms
- Eight Queens Problem
- Knight's Tour
- Selections and Permutations
- Selections with Loops
- Selections with Duplicates
- Selections Without Duplicates
- Permutations with Duplicates
- Permutations Without Duplicates
- Round-Robin Scheduling
- Recursion Removal
- Tail Recursion Removal
- Dynamic Programming
- Bottom-Up Programming
- General Recursion Removal
- Summary
- Exercises
- Tree Terminology
- Binary Tree Properties
- Tree Representations
- Tree Traversal
- Sorted Trees
- Lowest Common Ancestors
- Threaded Trees
- Specialized Tree Algorithms
- Interval Trees
- Summary
- Exercises
- AVL Trees
- 2-3 Trees
- B-Trees
- Balanced Tree Variations
- Summary
- Exercises
- Searching Game Trees
- Searching General Decision Trees
- Swarm Intelligence
- Summary
- Exercises
- Network Terminology
- Network Representations
- Traversals
- Strongly Connected Components
- Finding Paths
- Transitivity
- Shortest Path Modifications
- Summary
- Exercises
- Topological Sorting
- Cycle Detection
- Map Coloring
- Maximal Flow
- Network Cloning
- Cliques
- Community Detection
- Eulerian Paths and Cycles
- Summary
- Exercises
- Matching Parentheses
- Pattern Matching
- String Searching
- Calculating Edit Distance
- Phonetic Algorithms
- Summary
- Exercises
- Terminology
- Transposition Ciphers
- Substitution Ciphers
- Block Ciphers
- Public-Key Encryption and RSA
- Other Uses for Cryptography
- Summary
- Exercises
- Notation
- Complexity Classes
- Reductions
- 3SAT
- Bipartite Matching
- NP-Hardness
- Detection, Reporting, and Optimization Problems
- Detection ≤p Reporting
- Reporting ≤p Optimization
- Reporting ≤p Detection
- Optimization ≤p Reporting
- Approximate Optimization
- NP-Complete Problems
- Summary
- Exercises
- Types of Parallelism
- Distributed Algorithms
- Summary
- Exercises
- Asking Interview Puzzle Questions
- Answering Interview Puzzle Questions
- Summary
- Exercises
- Lesson 1: Algorithm Basics
- Lesson 2: Numeric Algorithms
- Lesson 3: Linked Lists
- Lesson 4: Arrays
- Lesson 5: Stacks and Queues
- Lesson 6: Sorting
- Lesson 7: Searching
- Lesson 8: Hash Tables
- Lesson 9: Recursion
- Lesson 10: Trees
- Lesson 11: Balanced Trees
- Lesson 12: Decision Trees
- Lesson 13: Basic Network Algorithms
- Lesson 14: More Network Algorithms
- Lesson 15: String Algorithms
- Lesson 16: Cryptography
- Lesson 17: Complexity Theory
- Lesson 18: Distributed Algorithms
- Lesson 19: Interview Puzzles
Hands on Activities (Performance Labs)
- Discussing about Algorithms, Numerical Algorithms, and Arrays
- Learning Common Run Time Functions
- Understating about Big O Notation
- Creating Pseudorandom Numbers
- Making Random Walks
- Calculating Greatest Common Divisors
- Testing of Primality
- Performing Numerical Integration
- Using Back Substitution
- Finding Cells
- Discussing about Arrays, Stacks and Queues, and Sorting
- Finding Median
- Finding Average
- Learning about Array Types
- Adding Matrices
- Reversing An Array
- Understanding Stacks
- Understanding Queues
- Merging Trees
- Understanding Binomial Trees
- Understanding the Heap Sort Algorithm
- Understanding Sorting Algorithm
- Summarizing the Algorithms
- Understanding the Linear Search Algorithm
- Understanding Binary Search
- Understanding Interpolation Search
- Discussing about Searching, Hash Tables, and Recursion
- Understanding Open Addressing
- Understanding the Factorial
- Learning about the Koch Curves
- Understanding Eight Queens Problem
- Understanding about Balanced and Decision Trees
- Understanding Tree Terminology
- Calculating Number of Nodes
- Learning About Tree Traversal
- Deleting Values
- Understanding Random Search
- Understanding Network Terminology
- Using the Brute Force Approach
- Understanding Pattern Matching
- Discussing about Network and String Algorithms
- Calculating the Euler's Totient Function
- Discussing about Cryptography, Complexity Theory, and Distributed Algorithms
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