Data Management for Retail Dataset using Python and Pandas paid course free. You will get to learn about the approach that is used to develop the data management based solution
- You will get to learn about the approach that is used to develop the data management based solution. To complete the projects, you will be working using python and all the libraries that we got covered in this training.
- we will be using the concepts covered in the course to develop the solution. You will get to learn about various new concepts in this project and will also master the topics that revolve around data analytics.
Data Management for Retail Dataset using Python and Pandas Course Requirements
- Basic understanding of Computer Programming terminologies.
- Basic understanding of any of the programming languages is a plus.
- Basic knowledge of Python and Mathematics
- No prior information for machine learning is needed.
Data Management for Retail Dataset using Python and Pandas Course Description
Pandas is a BSD-licensed open source Python library that provides high-performance, easy-to-use data structures and data analysis tools for the Python programming language. This Python course will help you start using Python for data analysis and visualization. This course has a project that will be based on data analysis case studies and data exploration. In this project, we will use the concepts covered in the course to develop solutions.
You will learn about several new concepts in this project, and you will also master the topics surrounding data analysis. The data management of the retail dataset will be the next major project of this training. You will learn about the methods used to develop solutions based on data management.
To complete these projects, you will use Python and all the libraries we cover in this training. Panda and NumPy are a Python library, and NumPy helps by contributing numerical and computational work. On the other hand, Panda is more suitable for work related to data manipulation and data manipulation. Both NumPy and Panda constitute the scientific language of Python. The ability to manipulate matrices and vectors can be found using the NumPy and Panda libraries (which we call essential).
NumPy stands for Numeric Python, an open source framework that meets the needs of mathematics. A necessary matrix for advanced math functions. NumPy is related to machine learning in Scikit-learn, Pandas, Matplotlib, and TensorFlow. On the other hand, Panda provides similar functionality in machine learning and is the most widely used Python library. It is easy to use, easy to build, and provides high performance. It is an excellent data analysis tool.
Who this course is for:
- Anyone who wants to learn the basics and various functions of Pandas.
- Data Engineers, Architects, Analysts, Software Engineers, IT operations, Technical Managers, Data Scientists