Python with NumPy For Absolute Beginners
What you'll learn
- Understanding Python Numpy basics in just 2 hours
- Understanding Lists are different from arrays
- Implementing array operations using Numpy module in python
- Searching and sorting operations in Arrays
- Python Programming
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.
Surendra Varma Pericherla
Who this course is for:
- Engineering Students, Software Developers And Aspiring Data Scientists
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 15+ Years of experience in Computer Science. (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 170 different countries.
"He loves education and educating others. His goal is to Provide quality of education to the students across the world."