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We’ll explore the concepts and code behind computer science topics that are fundamental knowledge for any programmer as well as popular job interview questions.
Part 1 of the workshop will focus on big O notation, recursion, and the binary search algorithm.
Part 2 will focus on data structures - determining their efficiency, the benefits and tradeoffs of different structures, and implementing a hash table.
Part 1: - Analyze algorithms to determine their Big O complexity. - Explain the difference between brute force search and binary search. - Implement the binary search algorithm.
Part 2: - Determine when different data structures should be used and why. - Analyze data structures to determine their Big O complexity for basic functions. - Implement a hash table.
Complete the computer science learning paths on myGA.
Part 1 key lessons: - Algorithms learning path: - Introduction to Algorithms - Big O Notation - Recursion - Introduction to Sorting - Basic Sorting Algorithms - Divide-and-Conquer Sorting Algorithms - Distribution Sorting Algorithms - Search Algorithms
Part 2 key lessons: - Data Structures learning path: - Introduction to Data Structures - Linked Lists - Stacks and Queues - Introduction to Hash Tables - Hash Tables Deep Dive - Sets - Binary Trees and Tries - Balancing Binary Trees - Graphs
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