Algorithms

Algorithms are a set of detailed instructions or rules designed to achieve a specific outcome or solve a particular problem, often within the realm of computer programming. Coursera's algorithm catalogue guides you in understanding, constructing, and applying algorithms effectively. You'll learn about algorithmic paradigms like divide and conquer, dynamic programming, and greedy algorithms, as well as data structures that support these algorithms. Additionally, you will understand the principles of algorithm complexity, allowing you to create more efficient and effective algorithms. This knowledge will be beneficial whether you're a budding programmer, a seasoned software engineer, or someone interested in enhancing their problem-solving skills in the digital landscape.
73credentials
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Results for "algorithms"

  • Skills you'll gain: Relational Databases, User Research, Probability & Statistics, Data Storytelling, Bash (Scripting Language), Graph Theory, Theoretical Computer Science, Object Oriented Design, Operating Systems, Android Development, Database Design, Encryption, Bioinformatics, Java Programming, Feature Engineering, Algorithms, TCP/IP, Version Control, Data Structures, Model View Controller

  • Skills you'll gain: Package and Software Management, Time Series Analysis and Forecasting, Relational Databases, Data Structures, Linear Algebra, Cloud Computing Architecture, Data Warehousing, Database Management, Data Visualization, Social Network Analysis, Algorithms, Deep Learning, Portfolio Management, Oral Comprehension, Java Programming, Dimensionality Reduction, Matplotlib, Econometrics, R Programming, Pivot Tables And Charts

  • Skills you'll gain: Database Design, Enterprise Architecture, Data Governance, Database Theory, User Research, Stakeholder Engagement, Lean Methodologies, Algorithms, Database Management, Process Mapping, Unified Modeling Language, Process Analysis, Object Oriented Design, Software Architecture, Responsive Web Design, Cascading Style Sheets (CSS), Agile Methodology, Object Oriented Programming (OOP), Data Structures, Data Ethics

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