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  • Understanding Python Numpy basics in just 1.5 hours
  • Implementing array operations using Numpy module in python
  • Searching and sorting operations in Arrays

NumPy is a basic level external library in Python used for complex mathematical operations. NumPy overcomes slower executions with the use of multi-dimensional array objects. It has built-in functions for manipulating arrays. We can convert different algorithms to can into functions for applying on arrays. NumPy has applications that are not only limited to itself. It is a very diverse library and has a wide range of applications in other sectors. Numpy can be put to use along with Data Science, Data Analysis and Machine Learning. It is also a base for other python libraries. These libraries use the functionalities in NumPy to increase their capabilities.

 

This course introduce with all majority of concept of NumPy - numerical python library.

You will learn following topics :

1) Creating Arrays using Numpy in Python

2) Accessing Arrays using Numpy in Python

3) Finding Dimension of the Array using Numpy in Python

4) Negative Indexing on Arrays using Numpy in Python

5) Slicing an Array using Numpy in Python

6) Checking Datatype of an Array using Numpy in Python

7) Copying an Array using Numpy in Python

8) Iterating through arrays using Numpy in Python

9) Shape of Arrays using Numpy in Python

10) Reshaping Arrays using Numpy in Python

11) Joining Arrays using Numpy in Python

12) Splitting Array using Numpy in Python

13) Sorting an Array using Numpy in Python

14) Searching in Array using Numpy in Python

15) Filtering an Array using Numpy in Python

16) Generating a Random Array using Numpy in Python

 

 

Arrays in Numpy are equivalent to lists in python. Like lists in python, the Numpy arrays are homogenous sets of elements. The most important feature of NumPy arrays is they are homogenous in nature. This differentiates them from python arrays. It maintains uniformity for mathematical operations that would not be possible with heterogeneous elements. Another benefit of using NumPy arrays is there are a large number of functions that are applicable to these arrays. These functions could not be performed when applied to python arrays due to their heterogeneous nature.

 

 

 

Happy learning

Surendra Varma Pericherla.

  • Python Programming
  • Engineering Students
  • Software Developers
  • Aspiring Data Scientists
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  • Section 1 : Working with 1D arrays 3 Lectures 00:05:34

    • Lecture 1 :
    • Creating & Accessing elements in 1D Array Preview
    • Lecture 2 :
    • Using Negative Indexing to access elements in 1D array
    • Lecture 3 :
    • Iterating 1D arrays
  • Section 2 : Working with 2D arrays 3 Lectures 00:08:44

    • Lecture 1 :
    • Creating & Accessing elements in 2D Array
    • Lecture 2 :
    • Using Negative Indexing to access elements in 2D array
    • Lecture 3 :
    • Iterating 2D arrays
  • Section 3 : Operations on arrays 13 Lectures 00:45:46

    • Lecture 1 :
    • Finding Dimension of the Array
    • Lecture 2 :
    • Slicing an Array
    • Lecture 3 :
    • Checking Datatype of an array
    • Lecture 4 :
    • Copy operation on an array
    • Lecture 5 :
    • Getting shape of an array
    • Lecture 6 :
    • Reshaping 1D array to 2D array
    • Lecture 7 :
    • Joining two arrays
    • Lecture 8 :
    • Splitting an array
    • Lecture 9 :
    • Sorting an Array
    • Lecture 10 :
    • Searching for an element in array
    • Lecture 11 :
    • Filtering an array
    • Lecture 12 :
    • Generating a random integer
    • Lecture 13 :
    • Generating a random array
  • Section 4 : Test your knowledge on Numpy 12 Lectures 00:12:03

    • Lecture 1 :
    • Question #1
    • Lecture 2 :
    • Solution to Question #1
    • Lecture 3 :
    • Question #2
    • Lecture 4 :
    • Solution to Question #2
    • Lecture 5 :
    • Question #3
    • Lecture 6 :
    • Solution to Question #3
    • Lecture 7 :
    • Question #4
    • Lecture 8 :
    • Solution to Question #4
    • Lecture 9 :
    • Question #5
    • Lecture 10 :
    • Solution to Question #5
    • Lecture 11 :
    • Question #6
    • Lecture 12 :
    • Solution to Question #6
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The name of the instructor is Surendra varma. He is a winner of  BEST TEACHER award. He is a winner of  Young Achiever award. He holds Bachelors degree in Computer Science & Masters degree in Computer science. He cracked toughest exams in computer science such as GATE & UGC-NET with flying colors. Also, he is a university topper during masters. He is currently Pursuing PhD from world's most reputed university Indian Institute of Sciences(IISC), Bangalore. He worked with various EdTech companies in India including Great Learning. He always received best feedback from his students. He has 14+ Years of experience in Teaching/research/Industry. He worked in various roles like Software Engineer, Associate professor, Researcher, Technical Trainer, Senior Technical Trainer, Technical head & Academic head. He has trained over 1,00,000 students in his career. His former students are currently working in MNC's such as Amazon, Infosys, Wipro, TCS, CTS, Accenture etc. He has given Guest lectures in top Universities/ colleges in India like IIIT’s, SRM University, VIT etc. He has given online training to students of various countries such as India, USA, Canada, UAE, Australia, UK, Germany etc. He ranked in Top 5% in Cracking the Amazon Coding Assessment. In Udemy, his students are scattered in 150 different countries. "He loves education and educating others. His goal is to Provide quality of education to the students across the world."
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