Course Introduction This course is designed for placement preparation and will m

Course Introduction
This course is designed for placement preparation and will mainly cover data structures and algorithms using C and C++. Even if you do not know C++, you will still be able to follow along easily. The notes will be made available as a PDF in the description below.
Data Structures and Algorithms
Data structures are used to arrange data in main memory for efficient usage while algorithms are a sequence of steps to solve a given problem. In this course, we will cover arrays, linked lists, and graphs as examples of data structures and dive into solving problems using different algorithms.
Programming Languages
C and C++ will be the primary languages used in this course but Java can also be used to implement the algorithms. I do not recommend Python or JavaScript for beginners but rather suggest learning C to get a solid foundation in programming.
Conclusion
Learning data structures and algorithms is a responsibility and I will teach this course in a way that is easy to understand for beginners. Don’t worry if you make mistakes or have trouble at first, just follow along step by step and everything will become clear.
Data Structures & Algorithms for Placements
This course is primarily for those preparing for placements or job interviews.
Time is limited when preparing for placements, so this course is structured to value your time. A 15-hour video on C with notes is available on the channel, which will be covered first. If you’re an advanced Java user or can program algorithms in Python, then it’s possible to do so. However, it’s recommended to learn C and C++ first.
Data structure is an arrangement of data in main memory, which refers to RAM (Random Access Memory) of 2, 4, 8, 16, or 32 GB. The sequence of RAM usage is important when loading a program like “chrome.exe” for Windows. Fiddling with data occurs in main memory, which must be arranged optimally using data structures to minimize RAM usage.
The theory of databases is not covered in this course, but you should know their basic concepts. When opening a new tab, a large amount of data is stored in a database that must be retrieved and updated regularly. Data warehouses store data permanently for faster retrieval and updation for analysis purposes. Legacy data needs to be stored separately from the main system.
Sorting Algorithms
The example used here is sorting arrays in ascending or descending order. An algorithm is a series of steps to create a process. When sorting an array, steps must be taken to sort in ascending or descending order. The steps taken to sort an algorithm into an array define the algorithm.
Data Warehousing and Big Data
Data is the fuel of big algorithms these days, so it’s essential not to lose the data. To prevent data loss, the data is separated from the main system and stored in what is known as legacy data. Data warehousing, on the other hand, deals with how to store legacy data efficiently in different types of algorithms, analysis, and distributed systems that can handle huge databases that regular applications or algorithms cannot. Big data is a separate field that requires a different set of algorithms and analysis.
It’s essential to understand data warehousing and big data, though they are beyond the scope of this course. Do not use these terms, but understand their significance. The best way to learn data structures and algorithms is to study C programming, specifically stacks and heaps. In the context of C programming, understand that the memory layout of a C program is divided into segments, such as the stack, heap, and segments for static and global variables.
Memory Layout of a C Program
The stack frame or activation record of the main function is always created first, and subsequent activation records of other functions such as fun1 and fun2 are created when called. Variables are created in their respective activation records. To better understand memory usage, think of it as “looking back at your memory” and “reading your memory back from the page” to see what you need to access. Understanding memory usage helps you to be able to optimize your algorithms and take full advantage of available resources.
Understanding Heap Memory
When writing code, variables are stored in memory in a space called the stack. As functions are called, these variables are added to the stack and are removed once the functions have completed execution. However, in addition to the stack, there is also a space called the heap, which can be used to allocate memory dynamically through the use of pointers.
Pointer Basics
A pointer is a variable that stores the address of a memory location. In C, you can use the malloc function to request dynamic memory in the heap, while in C++, you can use the new operator. You use pointers to request the memory and to access it later.
Heap Memory
The heap is a large pool of memory in your computer’s RAM that can be allocated using a pointer. By requesting memory from the heap, you can store more complex data structures than you would be able to in the stack.
Time and Space Complexity
Efficient use of memory is an important part of writing algorithms and data structures. Using the heap is one way to optimize your code and use memory more efficiently. Time and space complexity are both important considerations when designing algorithms.
This is how the C program is run inside our memory. In the coming videos, we will focus on data structures and algorithms.
It is a prerequisite to know a little bit about it. I will use these terms, and understanding of this is necessary when we will see linked list, array, and binary search tree.
I recommend learning C and C++ to prepare data structures and algorithms for any product-based company.
I have made a 15-hour long video of C with notes the way I have given this video with notes. I hope you like this video. If you don’t know C properly, then I have a 15-hour long video. You must definitely learn this.
When you go for an interview, then the person in front of you will expect C, C++, or Java from you. You must know one of these three languages. You will be taken lightly over there. If you are only a Python and JavaScript programmer, then you will be at a disadvantage. You will still be down in front of a person who knows C, and I have written all these things in notes so you won’t have any problem.
I am telling this from experience. This is also a mindset, and you should do C and not to use Python and to be a programmer who knows it. I have also given their reasons in many more videos. I have said that you have to be careful about it. You have to use it. I’m not to be afraid of it.
If you want to use C and to understand it, it’s not to ignore it. In many of the most important to understand. You need to use the language. You need to understand what you need it. There is no need to be an expert. You should be aware of the problem.
You don’t know that you know that it’s not to make mistakes. You can be very aware of what you’ve got to understand the problem. Don’t be afraid to use a problem. You’re not to get to understand this. It’ll be very careful. It has to be aware that you are aware of it. It’s a very important. It’s a very good thing.
You know that the time complexity is a complex concept of time complexity. The video was created to explore time complexity and other topics in the coming videos.
Don’t forget to like this video. Tell me in the comment below how was this video, and I will see you next time.
The next video will be a time complexity video with notes and video of the time complexity. In the next video also with notes. Therefore, do access it guys. The other video is a time-com complexity video that explores time complexity, time complexity. The same way, I have given that video also with notes.
We will also explore the topics in our next videos. The next videos will be available in the following videos the next week. We are happy to see you in the new videos.
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