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Sriram Sankaranarayanan
Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data.
Read more
Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data.
Read more
Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data.
Trees and Graphs: Basics can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Register for this course and see more details by visiting:
OpenCourser.com/course/i8v24i/trees
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Syllabus
Binary Search Trees and Algorithms on Trees
In this module, you will learn about binary search trees and basic algorithms on binary search trees. We will also become familiar with the problem of balancing in binary search trees and study some solutions for balanced binary search trees such as Red-Black Trees.
Read more
Syllabus
Binary Search Trees and Algorithms on Trees
In this module, you will learn about binary search trees and basic algorithms on binary search trees. We will also become familiar with the problem of balancing in binary search trees and study some solutions for balanced binary search trees such as Red-Black Trees.
Read more
Basics of Graphs and Graphs Traversals
In this module, you will learn about graphs and various basic algorithms on graphs such as depth first/breadth first traversals, finding strongly connected components, and topological sorting.
Union-Find Data Structures and Spanning Tree Algorithms
Union Find Data-structure with rank compression.
Spanning trees and properties of spanning trees.
Prim’s algorithm for finding minimal spanning trees.
Kruskal’s algorithm for finding minimal spanning trees.
Shortest Path Algorithms
In this module, you will learn about:
Shortest Path Problem: Basics.
Bellman-Ford Algorithm for single source shortest path.
Dijkstra’s algorithm.
Algorithms for all-pairs shortest path problem (Floyd-Warshall Algorithm)
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a comprehensive overview of advanced data structures and algorithms essential for data scientists and computer scientists
Suitable for students with experience in basic data structures and algorithm concepts
Taught by an experienced and recognized instructor in the field of computer science
Emphasizes practical applications of data structures and algorithms in the real world
Aligned with the requirements of the MS in Data Science from CU Boulder, a reputable university
May require additional prerequisite knowledge for students with limited exposure to data structures and algorithms
Save this course
Save Trees and Graphs: Basics to your list so you can find it easily later:
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Reviews summary
Trees and graphs made simple
According to students, Trees and Graphs: Basics provides a strong foundation of theoretical knowledge and real-world implementation. Engaging assignments and detailed lectures help students understand key concepts, like MST and shortest path algorithms. While some typos and assignment quality inconsistencies have been noted, the well-structured course content and knowledgeable instructor make it a highly recommended choice for those seeking a deep dive into trees and graphs.
Assignments are well-designed and reinforce concepts, but vary in quality.
"...programming assignments are good and they make you appreciate more the lessons."
"The only problem is last week's assignment in my opinion."
"Assignments were fun also"
Lectures and readings effectively supplement each other to provide a comprehensive understanding.
"Excellent content. Lectures along with textbook provide student with working knowledge of trees and graphs."
"The readings supplement the lectures nicely."
"This is probably the closest you can get to a univesity course in Data Structures and Algorithms."
The instructor provides clear explanations and examples, making complex topics easier to grasp.
"Detailed lectures and thoroughly taught!"
"Excellent explanation of complex topics."
"This course is excellent. The instructor gives detailed, helpful lectures complete with clear examples..."
Some assignments could be improved for clarity or consistency in difficulty.
"...inconcistencies in the quality in programming assignments..."
"The final assignment seems extremely daunting at first glance..."
"Some typos are not acknowledged."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Trees and Graphs: Basics with these
activities:
Refresher: Asymptotic Analysis
Show steps
This will help you prepare for the mathematical rigor of this course
Browse courses on
Asymptotic Analysis
Show steps
-
Review time complexity concepts
-
Practice analyzing time complexity of common algorithms
Review of Introduction to Algorithms, 3rd Edition by Cormen, Leiserson, Rivest, and Stein
Show steps
Reinforce your understanding of the fundamental concepts of algorithms and data structures
View
Algorithms Unlocked (Mit Press)
on Amazon
Show steps
-
Read the book
-
Summarize key concepts
-
Solve practice problems
Visualize a binary search tree
Show steps
Will help you understand the insertion, deletion, and searching in a BST
Browse courses on
Binary Search Trees
Show steps
-
Draw a binary search tree with a given set of values
-
Perform insert, delete, and search operations on the tree
Four other activities
Expand to see all activities and additional details
Show all seven activities
Study group for graph theory
Show steps
Group study can clarify confusing material and improve understanding of concepts.
Browse courses on
Graph Theory
Show steps
-
Set up a study group meeting
-
Review course material together
-
Work on practice problems together
Graph Algorithms Problem Solving
Show steps
Will help familiarize you with common graph algorithms and their applications.
Browse courses on
Graph Algorithms
Show steps
-
Solve a variety of graph problems using depth first search
-
Solve a variety of graph problems using breadth first search
-
Solve a variety of graph problems using Dijkstra's algorithm
Write a blog post about a graph algorithm
Show steps
Create rich content that will help you master both the content and your writing abilities
Browse courses on
Graph Algorithms
Show steps
-
Research a graph algorithm
-
Write a outline
-
Write a draft
-
Edit and publish your blog post
Annotated Bibliography on graph algorithms
Show steps
Gain a deeper understanding of a specific graph algorithm by researching and summarizing findings.
Browse courses on
Graph Algorithms
Show steps
-
Research graph algorithms
-
Select relevant articles or papers
-
Read and annotate the selected resources
Refresher: Asymptotic Analysis
Show steps
This will help you prepare for the mathematical rigor of this course
Browse courses on
Asymptotic Analysis
Show steps
Show steps
Show steps
- Review time complexity concepts
- Practice analyzing time complexity of common algorithms
Review of Introduction to Algorithms, 3rd Edition by Cormen, Leiserson, Rivest, and Stein
Show steps
Reinforce your understanding of the fundamental concepts of algorithms and data structures
View
Algorithms Unlocked (Mit Press)
on Amazon
Show steps
Show steps
Show steps
- Read the book
- Summarize key concepts
- Solve practice problems
Visualize a binary search tree
Show steps
Will help you understand the insertion, deletion, and searching in a BST
Browse courses on
Binary Search Trees
Show steps
Show steps
Show steps
- Draw a binary search tree with a given set of values
- Perform insert, delete, and search operations on the tree
Four other activities
Expand to see all activities and additional details
Show all seven activities
Study group for graph theory
Show steps
Group study can clarify confusing material and improve understanding of concepts.
Browse courses on
Graph Theory
Show steps
Show steps
Show steps
- Set up a study group meeting
- Review course material together
- Work on practice problems together
Graph Algorithms Problem Solving
Show steps
Will help familiarize you with common graph algorithms and their applications.
Browse courses on
Graph Algorithms
Show steps
Show steps
Show steps
- Solve a variety of graph problems using depth first search
- Solve a variety of graph problems using breadth first search
- Solve a variety of graph problems using Dijkstra's algorithm
Write a blog post about a graph algorithm
Show steps
Create rich content that will help you master both the content and your writing abilities
Browse courses on
Graph Algorithms
Show steps
Show steps
Show steps
- Research a graph algorithm
- Write a outline
- Write a draft
- Edit and publish your blog post
Annotated Bibliography on graph algorithms
Show steps
Gain a deeper understanding of a specific graph algorithm by researching and summarizing findings.
Browse courses on
Graph Algorithms
Show steps
Show steps
Show steps
- Research graph algorithms
- Select relevant articles or papers
- Read and annotate the selected resources
Career center
Learners who complete Trees and Graphs: Basics will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. This course provides a strong foundation in the algorithms and data structures used in data science, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Data Scientist.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models. This course provides a strong foundation in the algorithms and data structures used in machine learning, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Machine Learning Engineer.
Business Analyst
Business Analyst
Business Analysts help businesses understand their data and make better decisions. This course provides a strong foundation in the algorithms and data structures used in business analysis, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Business Analyst.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical methods to solve business problems. This course provides a strong foundation in the algorithms and data structures used in operations research, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of an Operations Research Analyst.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course provides a strong foundation in the algorithms and data structures used in data analysis, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Data Analyst.
Database Administrator
Database Administrator
Database Administrators are responsible for managing and maintaining databases. This course provides a strong foundation in the algorithms and data structures used in database management, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Database Administrator.
Data Engineer
Data Engineer
Data Engineers design and build data pipelines. This course provides a strong foundation in the algorithms and data structures used in data engineering, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Data Engineer.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze data and make predictions. This course provides a strong foundation in the algorithms and data structures used in quantitative analysis, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Quantitative Analyst.
Computer Scientist
Computer Scientist
Computer Scientists design, develop, and analyze algorithms and data structures. This course provides a strong foundation in the algorithms and data structures used in computer science, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Computer Scientist.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides a strong foundation in the algorithms and data structures used in software engineering, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Software Engineer.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This course provides a strong foundation in the algorithms and data structures used in statistics, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Statistician.
User Experience Researcher
User Experience Researcher
User Experience Researchers conduct research to understand how users interact with products and services. This course provides a strong foundation in the algorithms and data structures used in user experience research, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a User Experience Researcher.
Market Researcher
Market Researcher
Market Researchers collect, analyze, and interpret data to understand consumer behavior and market trends. This course provides a strong foundation in the algorithms and data structures used in market research, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Market Researcher.
Actuary
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. This course provides a strong foundation in the algorithms and data structures used in actuarial science, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of an Actuary.
Financial Analyst
Financial Analyst
Financial Analysts use mathematical and statistical methods to analyze financial data and make investment recommendations. This course provides a strong foundation in the algorithms and data structures used in financial analysis, which are essential for success in this role. Specifically, the modules on binary search trees, graph traversal algorithms, and shortest path algorithms are particularly relevant to the work of a Financial Analyst.
For more career information including salaries, visit:
OpenCourser.com/course/i8v24i/trees
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Trees and Graphs: Basics.
Is commonly used as a textbook for undergraduate and graduate courses in algorithms. It covers algorithms commonly taught in computer science programs and their analyses.
Is commonly used as a textbook for undergraduate courses in data structures and algorithms. It covers data structures commonly implemented in Java and their algorithms.
Is commonly used as a textbook for undergraduate courses in algorithms. It covers algorithms commonly taught in computer science programs and their analyses. Also includes exercises and challenges for further learning and practice.
Provides simple and entertaining introductions to graph theory and tree theory. Can be used as a supplementary reading for the course.
Is commonly used as a textbook for undergraduate courses in data structures and algorithms. It covers data structures commonly implemented in Python and their algorithms.
Save
Covers algorithms commonly taught in computer science programs and their analyses. It also includes exercises and challenges for further learning and practice.
Provides a comprehensive introduction to graph theory with applications to engineering and computer science. It covers a wide range of graph theoretical concepts.
Provides a comprehensive introduction to discrete mathematics with applications to computer science. It covers a wide range of topics, including graph theory, trees, and algorithms.
Provides a concise and clear introduction to algorithms and data structures. It covers a wide range of topics, including trees, graphs, and sorting algorithms.
Provides a comprehensive introduction to graph theory with a focus on computer science applications. It covers a wide range of graph theoretical concepts.
Provides a comprehensive reference for graph theory. It covers a wide range of graph theoretical concepts, including trees, graphs, and algorithms.
Save
Provides a comprehensive introduction to graph theory. It covers a wide range of graph theoretical concepts, including trees, graphs, and algorithms.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/i8v24i/trees
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Effort
8-15 hours a week for 4 weeks
Level
Advanced
Via
Coursera
Institution
University of Colorado Boulder
Instructor
Sriram Sankaranarayanan
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
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Good to know
Provides a comprehensive overview of advanced data structures and algorithms essential for data scientists and computer scientists
Suitable for students with experience in basic data structures and algorithm concepts
Taught by an experienced and recognized instructor in the field of computer science
Emphasizes practical applications of data structures and algorithms in the real world
Aligned with the requirements of the MS in Data Science from CU Boulder, a reputable university
May require additional prerequisite knowledge for students with limited exposure to data structures and algorithms
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