ESS-ALGO.AE1
Essential Algorithms Using Python and C#
Explore computer algorithms for solving real-world problems using Python and C# programming language.
- Practice in 42 Laboratorios prácticos — nothing to install
- 21 Lecciones interactivas y 189 topics mapped to the official exam objectives
- 101 Preguntas del examen de práctica
Beginner A tu propio ritmo · 1 año de acceso 5.0/5 (15 Revisar)
42 LiveLabs prácticos
Practice real IT tasks in guided environments.
- Entornos reales
- Calificación automática
- Sin instalación
21Lecciones interactivas
189Topics
42Laboratorio en vivo
101Preguntas del examen de práctica
434Tarjetas didácticas
436Glosario de términos
01 / Habilidades que obtendrás
What you will be able to do
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No se requiere tarjeta de crédito
This course is about solving real-world problems following the principles of computer algorithms using Python and C# languages. Learn the fundamentals of Python algorithms (step-by-step instructions for solving problems) and data structures (organizing, storing, and accessing data). Explore a wide range of structures including arrays, linked lists, stacks, and queues. Learn how to measure an algorithm's most crucial complexities including how long it takes to run (time) and how much space it uses (space/memory). The course includes exercises and solutions that are useful for both students and professionals. It aims to help you prepare for programming job interviews that typically involve technical algorithm questions.
- Create algorithms to solve computational problems.
- Implementing data structures for storing and accessing data
- Expertly handling sorting algorithms like sort, merge sort, quicksort, and binary search
- Determining algorithm’s space and time complexities
- Learning advanced algorithms techniques like recursion, backtracking, and divide & conquer
- Gain confidence to answer computer algorithm related technical questions during job interviews
- Enhance your programming skills in both Python and C#
Course Highlights
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21 Lecciones estructuradas Cobertura completa de los objetivos principales del curso
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42 LiveLabs prácticos Escenarios interactivos guiados con evaluación instantánea
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101 Preguntas de práctica Pruebas de evaluación con justificaciones de respuesta detalladas
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1 año de acceso completo Aprendizaje a tu propio ritmo, accesible en cualquier momento y en todos los dispositivos
02 / Lecciones y laboratorios
See exactly what you will learn and practice
Plan de estudios
21 Lecciones interactivas · 189 topics01 Introduction 7 topics +
- 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
02 Algorithm Basics 7 topics · 3 Laboratorio en vivo +
- Approach
- Algorithms and Data Structures
- Pseudocode
- Algorithm Features
- Practical Considerations
- Summary
- Exercises
3 Laboratorio en vivo in this lesson — see the labs panel →
03 Numerical Algorithms 10 topics · 6 Laboratorio en vivo +
- Randomizing Data
- Finding Greatest Common Divisors
- Performing Exponentiation
- Working with Prime Numbers
- Performing Numerical Integration
- Finding Zeros
- Gaussian Elimination
- Least Squares Fits
- Summary
- Exercises
6 Laboratorio en vivo in this lesson — see the labs panel →
04 Linked Lists 10 topics · 1 Laboratorio en vivo +
- 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
1 Laboratorio en vivo in this lesson — see the labs panel →
05 Arrays 8 topics · 5 Laboratorio en vivo +
- Basic Concepts
- One-Dimensional Arrays
- Nonzero Lower Bounds
- Triangular Arrays
- Sparse Arrays
- Matrices
- Summary
- Exercises
5 Laboratorio en vivo in this lesson — see the labs panel →
06 Stacks and Queues 5 topics · 5 Laboratorio en vivo +
- Stacks
- Queues
- Binomial Heaps
- Summary
- Exercises
5 Laboratorio en vivo in this lesson — see the labs panel →
07 Sorting 5 topics · 3 Laboratorio en vivo +
- O(N2) Algorithms
- O(N log N) Algorithms
- Sub O(N log N) Algorithms
- Summary
- Exercises
3 Laboratorio en vivo in this lesson — see the labs panel →
08 Searching 6 topics · 4 Laboratorio en vivo +
- Linear Search
- Binary Search
- Interpolation Search
- Majority Voting
- Summary
- Exercises
4 Laboratorio en vivo in this lesson — see the labs panel →
09 Hash Tables 5 topics · 1 Laboratorio en vivo +
- Hash Table Fundamentals
- Chaining
- Open Addressing
- Summary
- Exercises
1 Laboratorio en vivo in this lesson — see the labs panel →
10 Recursion 28 topics · 3 Laboratorio en vivo +
- 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
3 Laboratorio en vivo in this lesson — see the labs panel →
11 Trees 11 topics · 4 Laboratorio en vivo +
- Tree Terminology
- Binary Tree Properties
- Tree Representations
- Tree Traversal
- Sorted Trees
- Lowest Common Ancestors
- Threaded Trees
- Specialized Tree Algorithms
- Interval Trees
- Summary
- Exercises
4 Laboratorio en vivo in this lesson — see the labs panel →
12 Balanced Trees 6 topics · 1 Laboratorio en vivo +
- AVL Trees
- 2-3 Trees
- B-Trees
- Balanced Tree Variations
- Summary
- Exercises
1 Laboratorio en vivo in this lesson — see the labs panel →
13 Decision Trees 5 topics · 1 Laboratorio en vivo +
- Searching Game Trees
- Searching General Decision Trees
- Swarm Intelligence
- Summary
- Exercises
1 Laboratorio en vivo in this lesson — see the labs panel →
14 Basic Network Algorithms 9 topics · 1 Laboratorio en vivo +
- Network Terminology
- Network Representations
- Traversals
- Strongly Connected Components
- Finding Paths
- Transitivity
- Shortest Path Modifications
- Summary
- Exercises
1 Laboratorio en vivo in this lesson — see the labs panel →
15 More Network Algorithms 10 topics · 1 Laboratorio en vivo +
- Topological Sorting
- Cycle Detection
- Map Coloring
- Maximal Flow
- Network Cloning
- Cliques
- Community Detection
- Eulerian Paths and Cycles
- Summary
- Exercises
1 Laboratorio en vivo in this lesson — see the labs panel →
16 String Algorithms 7 topics · 2 Laboratorio en vivo +
- Matching Parentheses
- Pattern Matching
- String Searching
- Calculating Edit Distance
- Phonetic Algorithms
- Summary
- Exercises
2 Laboratorio en vivo in this lesson — see the labs panel →
17 Cryptography 8 topics · 1 Laboratorio en vivo +
- Terminology
- Transposition Ciphers
- Substitution Ciphers
- Block Ciphers
- Public-Key Encryption and RSA
- Other Uses for Cryptography
- Summary
- Exercises
1 Laboratorio en vivo in this lesson — see the labs panel →
18 Complexity Theory 15 topics +
- 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
19 Distributed Algorithms 4 topics · 1 Laboratorio en vivo +
- Types of Parallelism
- Distributed Algorithms
- Summary
- Exercises
1 Laboratorio en vivo in this lesson — see the labs panel →
20 Interview Puzzles 4 topics +
- Asking Interview Puzzle Questions
- Answering Interview Puzzle Questions
- Summary
- Exercises
21 Appendix A: Summary of Algorithmic Concepts 19 topics +
- 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
Laboratorios prácticos Our edge
42 Laboratorio en vivos- Understanding Algorithm Complexity Through Graph Visualization
- 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
- Implementing Linear Search in an Unsorted Array
- 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
- Tracing Fibonacci Computation Using Dynamic Programming
- Understanding Open Addressing
- Understanding the Factorial
- Learning about the Koch Curves
- Understanding Eight Queens Problem
- Evaluating Binary Tree Properties and Structure
- 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
- Differentiating Cipher Techniques Based on Functionality
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03 / Preguntas frecuentes
Preguntas antes de empezar
What are the prerequisites for the Essential Algorithms using Python and C# course?+
It is an advanced level course that offers an all-inclusive study on Essential Algorithms. Knowledge of basic programming language and familiarity with elementary mathematical concepts like arithmetic and logarithms will help you understand better. If you don’t have considerable experience, you can always look up and study a bit to brush up your skills before starting the course.
Will I learn both Python and C# in this course?+
Yes, you’ll be learning both the programming languages.
Who is this Essential Algorithms course intended for?+
This course is designed for a broad spectrum of users who want to improve their problem-solving skills using algorithms. It is an ideal course for strengthening your programming skills and writing more efficient and optimized codes. All those wanting to gain a competitive-edge in technical round interviews can benefit greatly from this course.
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