Welcome to the self paced course, Algorithms: Design and Analysis! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience.

Welcome to the self paced course, Algorithms: Design and Analysis! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience.

Welcome to the self paced course, Algorithms: Design and Analysis, Part 2! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This course is an introduction to algorithms for learners with at least a little programming experience.

This course covers the theory of automata and languages. We begin with a study of finite automata and the languages they can define (the so-called "regular languages." Topics include deterministic and nondeterministic automata, regular expressions, and the equivalence of these language-defining mechanisms.

The course is based on the text Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, and Jeff Ullman, who by coincidence are also the instructors for the course.

Visual Studio is the integrated development environment (IDE) for finance and operations apps. Developers can create deployable packages that contain projects and elements that are stored as metadata. Developing in Visual Studio allows users to customize the finance and operations apps experience.

A great way to start in tech is by landing a position as an intern. But how do you that? To get there, you need to consider things like, crafting a resume and passing an intern interview. Once an intern, you want to make sure that position turns into a full-time position in tech.

AI’s popularity has resulted in numerous well-publicized cases of bias, injustice, and discrimination. Often these harms occur in machine learning projects that have the best of goals, developed by data scientists with good intentions. This course, the second in the data science ethics program for both practitioners and managers, provides guidance and practical tools to build better models and avoid these problems.

Concern about the harmful effects of machine learning algorithms and AI models (bias and more) has resulted in greater attention to the fundamentals of data ethics.

Enhance your JavaScript skills with a comprehensive guide covering intermediate topics, techniques, and best practices for effective coding.

STL - Standard Template Library in C++ : First Step towards Data Structures and Algorithms (DSA)

Learn how to write programs by using lists, and learn how to use the list properties and list functions that are specified in the list module.