Last Updated on December 21, 2022
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This MicroMasters program is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems through implementing over one hundred 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 have invested thousands of hours designing challenges as an alternative to multiple choice questions that you usually find in MOOCs. We believe in learning through application, especially when it comes to learning algorithms.
For each algorithm you develop and implement, we have 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.
Job Outlook
- The median salary for Software Development jobs in the US is $100,690 per year. (source: Bureau of Labour Statistics)
- Career prospects include software engineer, data scientist, and site reliability engineer.
MicroMasters Program Details
How To Earn The MicroMasters Credential
Complete and successfully earn a verified certificate in all 8 courses plus the capstone project course.
Take Your Credential To The Next Level
Learners who successfully earn the Algorithms and Data Structures MicroMasters Credential are eligible to apply for admission to the School of Individualized Study (SOIS) Master of Science in Professional Studies at Rochester Institute of Technology.
If a learner applies for admission to the SOIC Master of Science in Professional Studies program at Rochester Institute of Technology, and is accepted, the MicroMasters Credential will count towards 25% of the coursework required by this program.
Courses
Algorithmic Design and Techniques
View the Algorithmic Design and Techniques courseabout Algorithmic Design and Techniques
Data Structures Fundamentals
View the Data Structures Fundamentals courseabout Data Structures Fundamentals
Graph Algorithms
View the Graph Algorithms courseabout Graph Algorithms
NP-Complete Problems
String Processing and Pattern Matching Algorithms
View the String Processing and Pattern Matching Algorithms courseabout String Processing and Pattern Matching Algorithms
Dynamic Programming: Applications In Machine Learning and Genomics
View the Dynamic Programming: Applications In Machine Learning and Genomics courseabout Dynamic Programming: Applications In Machine Learning and Genomics
Graph Algorithms in Genome Sequencing
View the Graph Algorithms in Genome Sequencing courseabout Graph Algorithms in Genome Sequencing
Algorithms and Data Structures Capstone
View the Algorithms and Data Structures Capstone courseabout Algorithms and Data Structures Capstone
Data structures and algorithms in python
A beginner-friendly introduction to common data structures (linked lists, stacks, queues, graphs) and algorithms (search, sorting, recursion, dynamic programming) in Python. This course will help you prepare for coding interviews and assessments. Enroll now to start learning.
- Watch live hands-on coding-focused video tutorials
- Practice coding with cloud Jupyter notebooks
- Solve questions from real programming interviews
- Earn a verified certificate of accomplishment
Lesson 1 – Binary Search, Linked Lists and Complexity
- Linear and Binary Search
- Complexity and Big O Notation
- Linked Lists using Python Classes
Assignment 1 – Binary Search Practice
- Understand and solve a problem systematically
- Implement linear search and analyze it
- Optimize the solution using binary search
Lesson 2 – Binary Search Trees, Traversals and Recursion
- Binary trees, traversals, and recursion
- Binary search trees & common operations
- Balanced binary trees and optimizations
Assignment 2 – Hash Tables and Python Dictionaries
- Hash tables from scratch in Python
- Handling collisions using linear probing
- Replicating Python dictionaries
Lesson 3 – Sorting Algorithms and Divide & Conquer
- Bubble sort and Insertion Sort
- Merge sort using Divide & Conquer
- Quicksort and average complexity
Assignment 3 – Divide and Conquer Practice
- Implement polynomial multiplication
- Optimize using divide and conquer
- Analyze time and space complexity
Lesson 4 – Recursion and Dynamic Programming
- Recursion and memoization
- Subsequence and knapsack problems
- Backtracking and pruning
Lesson 5 – Graph Algorithms (BFS, DFS & Shortest Paths)
- Graphs, trees, and adjacency lists
- Breadth-first and depth-first search
- Shortest paths and directed graphs
Project – Step-by-Step Solution to a Programming Problem
- Pick an interesting coding problem
- Solve the problem step-by-step
- Document and present the solution
Lesson 6 – Python Interview Questions, Tips & Advice
- Practice questions and solutions
- Tips for solving coding challenges
- Advice for cracking coding interviews
Data structures and algorithms in python
The purpose of this article is to give you a panorama of data structures and algorithms in Python. This topic is very important for a Data Scientist in order to help him or her to design and solve machine learning models in a more effective way.
We will see together with practical examples the built-in data structures, the user-defined data structures, and last but not least I will introduce you to some algorithms like traversal algorithms, sorting algorithms, and searching algorithms.
The purpose of this article is to give you a panorama of data structures and algorithms in Python. This topic is very important for a Data Scientist in order to help him or her to design and solve machine learning models in a more effective way.
We will see together with practical examples the built-in data structures, the user-defined data structures, and last but not least I will introduce you to some algorithms like traversal algorithms, sorting algorithms, and searching algorithms.
A beginner-friendly introduction to common data structures (linked lists, stacks, queues, graphs) and algorithms (search, sorting, recursion, dynamic programming) in Python. This course will help you prepare for coding interviews and assessments. Enroll now to start learning.
- Watch live hands-on coding-focused video tutorials
- Practice coding with cloud Jupyter notebooks
- Solve questions from real programming interviews
- Earn a verified certificate of accomplishment
Lesson 1 – Binary Search, Linked Lists and ComplexityOpen →
- Linear and Binary Search
- Complexity and Big O Notation
- Linked Lists using Python Classes
Assignment 1 – Binary Search PracticeOpen →
- Understand and solve a problem systematically
- Implement linear search and analyze it
- Optimize the solution using binary search
Lesson 2 – Binary Search Trees, Traversals and RecursionOpen →
- Binary trees, traversals, and recursion
- Binary search trees & common operations
- Balanced binary trees and optimizations
Assignment 2 – Hash Tables and Python DictionariesOpen →
- Hash tables from scratch in Python
- Handling collisions using linear probing
- Replicating Python dictionaries
Lesson 3 – Sorting Algorithms and Divide & ConquerOpen →
- Bubble sort and Insertion Sort
- Merge sort using Divide & Conquer
- Quicksort and average complexity
Assignment 3 – Divide and Conquer PracticeOpen →
- Implement polynomial multiplication
- Optimize using divide and conquer
- Analyze time and space complexity
Lesson 4 – Recursion and Dynamic ProgrammingOpen →
- Recursion and memoization
- Subsequence and knapsack problems
- Backtracking and pruning
Lesson 5 – Graph Algorithms (BFS, DFS & Shortest Paths)Open →
- Graphs, trees, and adjacency lists
- Breadth-first and depth-first search
- Shortest paths and directed graphs
Project – Step-by-Step Solution to a Programming ProblemOpen →
- Pick an interesting coding problem
- Solve the problem step-by-step
- Document and present the solution
