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Our Courses
Data Science Foundations: Data Structures and Algorithms
Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, searching, and indexing. …
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Course by
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Self Paced
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English
Object Oriented Java Programming: Data Structures and Beyond
This Specialization covers intermediate topics in software development. You’ll learn object-oriented programming principles that will allow you to use Java to its full potential, and you’ll implement data structures and algorithms for organizing large amounts of data in a way that is both efficient and easy to work with. You’ll also practice critically evaluating your own code, and you’ll build technical communication skills that will help you prepare for job interviews and collaborative work as a software engineer.
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Course by
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Self Paced
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English
Accelerated Computer Science Fundamentals
Topics covered by this Specialization include basic object-oriented programming, the analysis of asymptotic algorithmic run times, and the implementation of basic data structures including arrays, hash tables, linked lists, trees, heaps and graphs, as well as algorithms for traversals, rebalancing and shortest paths. This Specialization sequence is designed to help prospective applicants prepare for the flexible and affordable Online Master of Computer Science (MCS) and MCS in Data Science.
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Course by
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Self Paced
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English
Determine Shortest Paths Between Routers Using Python
By the end of this project you will use the adjacency list data structure and other data structures to find the shortest distance between a set of routers loaded from a file. The shortest path problem is well known in the field of computer science. An adjacency list is probably the best data structure to represent a set of connected vertices to find the shortest path from one vertex to another. One application for shortest paths is in mapping.
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Course by
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Self Paced
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3 hours
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English
Java FullStack Developer
Introducing the Java FullStack Developer Specialization, designed to empower your software development career by providing a comprehensive skillset for building integrated, cloud-ready web applications. The specialization consists of three intensive courses: Fundamentals of Java Programming: Understanding of core Java programming concepts and principles Proficiency in object-oriented programming principles such as inheritance, polymorphism, and abstraction Gaining knowledge in advanced Java topics like multi-threading, concurrency, and the application of common data structures Front-End for
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Course by
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Self Paced
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English
Computer Forensics
This three part InfoSec Specialization covers a wide variety of Computer Forensics topics. In the Digital Forensics Concepts course, you will learn about legal considerations applicable to computer forensics and how to identify, collect and preserve digital evidence. This course dives into the scientific principles relating to digital forensics and gives you a close look at on-scene triaging, keyword lists, grep, file hashing, report writing and the profession of digital forensic examination.
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Course by
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Self Paced
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English
Python Basics
This course introduces the basics of Python 3, including conditional execution and iteration as control structures, and strings and lists as data structures. You'll program an on-screen Turtle to draw pretty pictures. You'll also learn to draw reference diagrams as a way to reason about program executions, which will help to build up your debugging skills. The course has no prerequisites.
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Course by
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Self Paced
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34 hours
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English
Python Data Structures
This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis. This course will cover Chapters 6-10 of the textbook “Python for Everybody”. This course covers Python 3.
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Course by
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Self Paced
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3 hours
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English
Algorithms for DNA Sequencing
We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets.
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Course by
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Self Paced
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12 hours
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English
Data-driven Astronomy
Science is undergoing a data explosion, and astronomy is leading the way. Modern telescopes produce terabytes of data per observation, and the simulations required to model our observable Universe push supercomputers to their limits. To analyse this data scientists need to be able to think computationally to solve problems. In this course you will investigate the challenges of working with large datasets: how to implement algorithms that work; how to use databases to manage your data; and how to learn from your data with machine learning tools.
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Course by
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Self Paced
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24 hours
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English
Building Web Applications in PHP
In this course, you'll explore the basic structure of a web application, and how a web browser interacts with a web server. You'll be introduced to the request/response cycle, including GET/POST/Redirect. You'll also gain an introductory understanding of Hypertext Markup Language (HTML), as well as the basic syntax and data structures of the PHP language, variables, logic, iteration, arrays, error handling, and superglobal variables, among other elements. An introduction to Cascading Style Sheets (CSS) will allow you to style markup for webpages.
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Course by
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Self Paced
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31 hours
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English
Data Structures and Design Patterns for Game Developers
This course is a stand-alone course that builds on the knowledge included in the C# Programming for Unity Game Development Specialization, so the course assumes you have the prerequisite knowledge from that Specialization. You should make sure you have that knowledge, either by taking those courses or from personal experience, before tackling this course.
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Course by
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Self Paced
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22 hours
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English
Programming in Python
In this course, you will be introduced to foundational programming skills with basic Python Syntax. You’ll learn how to use code to solve problems. You’ll dive deep into the Python ecosystem and learn popular modules, libraries and tools for Python. You’ll also get hands-on with objects, classes and methods in Python, and utilize variables, data types, control flow and loops, functions and data structures.
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Course by
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Self Paced
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45 hours
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English
Introduction to Data Engineering
Start your journey in one of the fastest growing professions today with this beginner-friendly Data Engineering course! You will be introduced to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in the ecosystem. You will begin this course by understanding what is data engineering as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in this exciting field.
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Course by
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Self Paced
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13 hours
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English
Build a Modern Computer from First Principles: Nand to Tetris Part II (project-centered course)
In this project-centered course you will build a modern software hierarchy, designed to enable the translation and execution of object-based, high-level languages on a bare-bone computer hardware platform. In particular, you will implement a virtual machine and a compiler for a simple, Java-like programming language, and you will develop a basic operating system that closes gaps between the high-level language and the underlying hardware platform. In the process, you will gain a deep, hands-on understanding of numerous topics in applied computer science, e.g.
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Course by
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Self Paced
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90 hours
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English
Data Structures and Performance
How do Java programs deal with vast quantities of data? Many of the data structures and algorithms that work with introductory toy examples break when applications process real, large data sets. Efficiency is critical, but how do we achieve it, and how do we even measure it? This is an intermediate Java course. We recommend this course to learners who have previous experience in software development or a background in computer science, and in particular, we recommend that you have taken the first course in this specialization (which also requires some previous experience with Java).
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Course by
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Self Paced
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42 hours
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English
Advanced Data Structures in Java
How does Google Maps plan the best route for getting around town given current traffic conditions? How does an internet router forward packets of network traffic to minimize delay? How does an aid group allocate resources to its affiliated local partners? To solve such problems, we first represent the key pieces of data in a complex data structure. In this course, you’ll learn about data structures, like graphs, that are fundamental for working with structured real world data. You will develop, implement, and analyze algorithms for working with this data to solve real world problems.
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Course by
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Self Paced
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29 hours
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English
Mastering the Software Engineering Interview
You’ve hit a major milestone as a computer scientist and are becoming a capable programmer. You now know how to solve problems, write algorithms, and analyze solutions; and you have a wealth of tools (like data structures) at your disposal. You may now be ready for an internship or (possibly) an entry-level software engineering job. But can you land the internship/job? It depends in part on how well you can solve new technical problems and communicate during interviews. How can you get better at this? Practice!
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Course by
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Self Paced
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21 hours
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English
Java Programming: Arrays, Lists, and Structured Data
Build on the software engineering skills you learned in “Java Programming: Solving Problems with Software” by learning new data structures. Use these data structures to build more complex programs that use Java’s object-oriented features. At the end of the course you will write an encryption program and a program to break your encryption algorithm. After completing this course, you will be able to: 1. Read and write data from/to files; 2. Solve problems involving data files; 3. Perform quantitative analyses of data (e.g., finding maximums, minimums, averages); 4.
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Course by
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Self Paced
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14 hours
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English
Data Structures
A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this online course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it.
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Course by
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Self Paced
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25 hours
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English
Introduction to Data Science in Python
This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively.
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Course by
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Self Paced
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35 hours
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English
VLSI CAD Part I: Logic
A modern VLSI chip has a zillion parts -- logic, control, memory, interconnect, etc. How do we design these complex chips? Answer: CAD software tools. Learn how to build thesA modern VLSI chip is a remarkably complex beast: billions of transistors, millions of logic gates deployed for computation and control, big blocks of memory, embedded blocks of pre-designed functions designed by third parties (called “intellectual property” or IP blocks). How do people manage to design these complicated chips?
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Course by
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Self Paced
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23 hours
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English
Ordered Data Structures
In this course, you will learn new data structures for efficiently storing and retrieving data that is structured in an ordered sequence. Such data includes an alphabetical list of names, a family tree, a calendar of events or an inventory organized by part numbers. The specific data structures covered by this course include arrays, linked lists, queues, stacks, trees, binary trees, AVL trees, B-trees and heaps. This course also shows, through algorithm complexity analysis, how these structures enable the fastest algorithms to search and sort data.
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Course by
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Self Paced
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19 hours
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English
Object-Oriented Data Structures in C++
This course teaches learners how to write a program in the C++ language, including how to set up a development environment for writing and debugging C++ code and how to implement data structures as C++ classes. It is the first course in the Accelerated CS Fundamentals specialization, and subsequent courses in this specialization will be using C++ as the language for implementing the data structures covered in class.
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Course by
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Self Paced
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21 hours
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English
Algorithms for Searching, Sorting, and Indexing
This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters. Algorithms for Searching, Sorting, and Indexing 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.
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Course by
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Self Paced
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35 hours
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English