Lecture 8: Artificial Intelligence
Introduction to artificial intelligence focusing on prompt engineering, generative AI, decision trees, minimax, machine learning, deep learning, and large language models.
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Introduction to artificial intelligence focusing on prompt engineering, generative AI, decision trees, minimax, machine learning, deep learning, and large language models.
Introduction to computer science focusing on computational thinking, problem solving, representation, algorithms, pseudocode, Scratch, functions, variables, conditionals, and loops.
Introduction to the C programming language focusing on source code, machine code, compiler, correctness, design, style, Visual Studio Code, types, conditionals, variables, loops, Linux, GUI, CLI, constants, comments, pseudocode, operators, integer overflow, and floating-point imprecision.
Course recap focusing on programming skills, problem solving, and final project guidance.
Introduction to arrays focusing on preprocessing, compiling, assembling, linking, debugging, arrays, strings, command-line arguments, and cryptography.
Introduction to algorithms focusing on searching, linear search, binary search, sorting, bubble sort, selection sort, merge sort, and asymptotic notation.
Introduction to memory management focusing on pointers, segmentation faults, dynamic memory allocation, stack, heap, buffer overflow, file I/O, and images.
Introduction to data structures focusing on abstract data types, queues, stacks, linked lists, trees, binary search trees, hash tables, and tries.
Introduction to the Python programming language focusing on functions, arguments, return values, variables, boolean expressions, conditionals, loops, modules, and packages.
Introduction to SQL focusing on tables, types, statements, constraints, indexes, keywords, functions, transactions, race conditions, and SQL injection attacks.