COURSE DESCRIPTION
A Python package called NumPy, often known as Numerical Python, provides support for sizable multi-dimensional arrays and matrices in addition to a vast array of sophisticated mathematical operations that may be performed on these arrays. Numerous other Python libraries for scientific computing, such as SciPy, Matplotlib, and Pandas, are built on top of NumPy.
The fundamental data structure in NumPy is an array. Although they are far quicker and more effective for numerical computations, they are comparable to Python lists. Any dimension and any kind of data, including texts, floats, integers, and complex numbers, can be stored in NumPy arrays. Learn about our other course at codingshikho.com
CERTIFICATION
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We will Cover the following Topics in my sessions : –
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
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Requirements
- Basic Python Proficiency:
You should have a good grasp of basic Python programming, including data types, variables, loops, conditionals, functions, and basic data structures like lists and dictionaries. NumPy is a Python library, and you'll need to write Python code to work with it.
- Understanding of Mathematical Concepts:
NumPy is primarily used for numerical and scientific computing, so having a fundamental understanding of mathematical concepts like linear algebra, calculus, and statistics can be very helpful.
- Python Libraries:
It's also beneficial to be familiar with other Python libraries, as NumPy is often used in conjunction with them. For example, Matplotlib for data visualization and SciPy for scientific computing are commonly used alongside NumPy.
- Advanced Math and Scientific Knowledge:
Depending on your specific use case, having a deeper understanding of advanced mathematical concepts or specific domain knowledge (e.g., physics, biology, economics) may be required.
- Practice:
To become proficient in NumPy, practice is key. Work on exercises and small projects that involve data manipulation and numerical computation using NumPy. The more you practice, the more comfortable you'll become with the library.
Features
- Instructor-Well-qualified and we choose them from industry. .
- Placement- 100%
- Residential room- well- Air-conditioned room , good food Availability, cloth cleaning services
- Project- Real world projects to learn and develops skills .
- Material - PDF , 90h classes, Friendly-environment and Videos .
Target audiences
- Gender- Male & Female
- Age- 15y to 60y
- Qualification- BCA, MCA ,B.Tech and B.Sc
- Hobbies- Interested in learning , problem solving , practicing and reading
- Experience - 0y-1y