Introduction to C Programming

Related lectures (52)

Introduces the fundamental concepts of pointers in C programming, emphasizing their utility for memory access and dynamic allocation.

Covers the arithmetic of pointers, the relationship between pointers and arrays, and the concept of buffer overflow in C programming.

Explains pointer arithmetic in C, focusing on memory manipulation and common pitfalls.

Explains operators and expressions in C, focusing on arithmetic, comparison, and logical operations.

Covers the definition and applications of pointers in C programming, emphasizing their role in memory management and generic programming.

Covers in-place tokenization in C, focusing on modifying strings directly to extract tokens.

Covers the fundamental concepts of C++ programming, focusing on structures, typedef, and data processing.

Explains pointers in C, focusing on their role as variables that store memory addresses and the importance of understanding memory management.

Explains dynamic memory allocation in C, focusing on the realloc function and its implications for managing memory effectively.

Explains the differences between mutable and immutable objects in Python, focusing on lists, sets, and their behaviors.

Covers the basics of file handling in C, common issues, and standard functions.

Delves into cells array revision and time measurement in C programming, led by the instructor.

Covers the basics of memory allocation in C, including passing parameters by value and reference, dynamic arrays, and strings.

Explains implementing an OCR program in C for sudoku number recognition.

Introduces functions and control structures in Python, emphasizing their importance for code organization and reusability.

Covers logical indexing in Matlab, focusing on manipulating arrays based on logical conditions.

Introduces LabVIEW programming basics, covering user interface, data types, file handling, and error management.

Covers the basics of programming in Python, focusing on practical skills and hands-on exercises.

Provides an overview of deep learning concepts, focusing on data, model architecture, and challenges in handling large datasets.

Covers the basics of compilation and C++ programming, including variables, functions, loops, and debugging.

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