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 fro m 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
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 fro m 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
