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 … [Read more...] about Object-Oriented Data Structures in C++
Software Development
Agile with Atlassian Jira
This course discusses common foundational principles and practices used by agile methodologies, providing you with a flexible set of tools to use in your role (e.g. product owner, scrum master, project manager, team member) on an agile team. Learn agile and lean principles, including kanban and scrum, and use Jira Software Cloud as the tool to apply hands-on exercises in these … [Read more...] about Agile with Atlassian Jira
Continuous Delivery & DevOps
Amazon famously delivers new code every 11.6 seconds. Just a few years ago, this was unthinkable: many ‘cutting edge’ firms would release software quarterly. When it comes to digital innovation, velocity is critical and many would say it’s the most reliable determinant of success. Bringing an organization to the state of the art (or even functional capability) in this … [Read more...] about Continuous Delivery & DevOps
Biology Meets Programming: Bioinformatics for Beginners
Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gently-paced introduction to our Bioinformatics Specialization … [Read more...] about Biology Meets Programming: Bioinformatics for Beginners
Machine Learning Modeling Pipelines in Production
In the third course of Machine Learning Engineering for Production Specialization, you will build models for different serving environments; implement tools and techniques to effectively manage your modeling resources and best serve offline and online inference requests; and use analytics tools and performance metrics to address model fairness, explainability issues, and … [Read more...] about Machine Learning Modeling Pipelines in Production
