Project.101: Advanced Data Structures and Algorithms using C, Salient Features

Salient Features: Advanced Data Structures, Trees and Algorithms

→ Live & Interactive Sessions: 100% live instructor-led classes online, making real-time discussions, pair programming, and instant feedback possible.

→ Focused Target Audience: Tailored exclusively for engineering students with 0-1 years of experience to bridge the gap between theoretical coding and software engineering.

→ Pure C Programing: Scratches off everything about the latest languages, requiring trainees to learn about CS basics in depth from scratch.

→ Linux Ecosystem: Taught entirely in Linux-based systems, familiarizing developers with command line usage, file I/O operations, and low-level programming.

→ Advanced Pointers Manipulation: Advanced practice with double pointers (**) and function pointers, required to manipulate trees without additional memory copies.

→ Memory Profiling Required: Mandatory profiling using valgrind; all written programs must pass rigorous checks and have zero memory leaks and no segmentation fault.

→ Debugging like Pros: Extensive practice with gdb, learning how to debug applications, analyze the memory addresses, and view the whole tree from the stack.

→ Code Compilation Practices: Teaching proper and advanced C programming by creating Makefiles, making code modular and easy to compile.

→ Asymptotic Notation: In-depth knowledge of Big O, Omega, and Theta notations used for proving mathematical efficiency of algorithms.

→ CPU-Time/Space tradeoff: Exercises and examples of code that demonstrates CPU cycles vs. memory constraints, such as caches and struct packing.

→ Algorithmic Paradigms: Competence in important programming approaches, such as Divide and Conquer, Dynamic Programming, Greedy Algorithms, and Backtracking.

→ Master Class of "10 Trees": Full, custom-built implementation of 10 extremely specialized trees.

Foundational Structures: Practice and reinforcement of recursion and iteration on Binary Search Trees (BST) and Binary Heap (Priority Queue).

→ Strictly Balanced Trees: Dealing with intricate balancing and pointer rotation of AVL Trees and Red-Black Trees.

→ Simulation of Database Indexes: Developing specialized B-Trees and B+ Trees to be highly effective at file I/O and disk reads.

→ String/Route Optimization: Creating multiway Tries (Prefix Trees) that enable fast autocomplete and routing algorithms.

→ Efficient Range Query: Constructing Segment Trees to work with intervals, summations of ranges, and geometrical calculations.

→ Randomized Trees: Learning about random priorities and adaptive algorithms using Treaps and Splay Trees.

→ Problem Modeling: Practical training in translating ambiguous, real-life business problems to algorithms.

→ EmbLogic Project: The last and final project, involving creating a full, in-memory and leak-proof Key-Value storage engine using the specialized trees mentioned above.