Data structures – Course Materials
Data Structures course gives you both theoretical and practical aspects of using various Abstract Data Types (ADTs). These ADTs include linked lists, stacks, queues, trees, hashing, searching, and sorting algorithms. When it comes to algorithms you are always faced with challenges with respect to space and time complexities, which this course covers in-depth. Based on the type and amount of data you are going to deal with, you will be in a position to choose the correct algorithm and implement it using the correct ADT. In short, you will see core computer science concepts getting applied.
From an implementation point of view, you will be extending your C programming course learning and making a deep dive into self-referential structures, dynamic memory allocation, and advanced pointer usage.
Get ready to write lengthy C programs and deal with segmentation fault / core dumps 
COURSE OBJECTIVES:
- Review methods for problem-solving and algorithm analysis
- Develop an understanding of Abstract Data Types (ADT) and their implementation
- Understand the importance of information hiding, data abstraction, and modular design
- Recognize programming needs – cost and benefits of each data structure
- Enable you to select the data structure for the given problem
TARGET AUDIENCE:
- Entry level engineers who want to learn Data Structure programming
- Experienced professionals who want to switch into development career
PREREQUISITE:
- Proficiency in C programming
- Good understanding of pointers in C
PLATFORM:
- OS – Linux (Ubuntu) / Windows / Mac
- Compiler – GCC (Preferred)
- Debugger – GDB (Preferred)
PRESENTATION SLIDES:
REFERENCE MATERIALS:
REFERENCE BOOKS:
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COMPLEXITY | MEDIUM |
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ASSIGNMENTS | 30 |
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PROJECTS | 3 |
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SAMPLE PROGRAMS | 18 |
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INTERVIEW PREP | COMING SOON |
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VIDEOS | COMING SOON |
Associated Courses |
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| C Programming | Deep dive into Advanced C programmig for embedded systems |
| C++ Programming | Learn OOPS with C++ for embedded systems |
| Python Programming | Built IoT Gateway with versatile Python |
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