What Level of Python is Required to Learn Data Science & Machine Learning?

Data Science is a multidisciplinary field that makes use of numerous techniques like Statistical Modeling, Python Programming, Machine Learning, Artificial Intelligence and more. Speaking of programming languages, Python is one of the most extensively used languages for Data Science operations. Being an open-source language, Python has a huge community base and is one of the most widely used programming languages today, In response to its efficiency and code readability, Python is also the most preferred programming language for expert Data Scientists. Despite of the stiff competition from R programming language, Python has become the backbone of many large-scale data analytical applications.

If you are curious about learning Python for Data Science then, you should know about the following important libraries.

Basic Libraries in Python for Data Science:

NumPy:

NumPy is one of the most extensively used library in Python for data analytical operations. If you are working on scientific computing in Python then working on NumPy would make the a lot easier. Also, most of the libraries in Python use NumPy arrays as their basic inputs and outputs. NumPy also has objects for multidimensional arrays and matrices which make it possible to perform mathematical and statistical functions on those arrays by simply writing just a few lines of code. 

Pandas

Extensive use of Pandas library in Python can be seen in the data analytical applications in finance, statistics, social sciences, and engineering. If you are handling incomplete, messy, and unlabeled data then Pandas is the best library to use as it supports data analysts with tools for shaping, merging, reshaping, and slicing datasets.

Matplotlib 

If you are looking for graphical representation of data then Matplotlib is the perfect option as it supports in the creation of 2D plots and graphs. It is very much flexible to use and you can make any kind of graph you want with matplotlib.

SciPy

If you are working on data manipulation or data visualization tasks then working on SciPy would be the perfect option as it has a number of algorithms and high-level commands that supports these operations..

Apart from libraries Python also has numerous tools that are needed for importing, analyzing, visualizing, and retrieving knowledge from large data sets. 

If you are also interested to build a career in Machine Learning then Data Science knowledge of data analysis isn’t sufficient. Python is a pre-requisite for Data Science and as well as for Machine Learning. You need to start with a solid knowledge of linear algebra and calculus, master a programming language like Python and master Scikit. 

Summary:

To work on Data Science models having knowledge of one or two programming languages is very crucial. Python is undoubtedly the best suited programming language for Data Science Python has numerous libraries such as Pandas, NumPy and Seaborn that can help in making sense out of the data. Python also has several packages that help in deploying Deep Learning or Machine Learning projects.

Python skills as they are applied in a variety of applications such as Data Analysis, Machine Learning And Data Mining. In this course you will learn all the basic concepts of python programming and a better understanding of how Python works in the field of Data Science. Master’s In Data Science Training program at AI Patasala focuses exclusively on teaching Python, AI, Machine Learning, Deep Learning Skills that are required to build a successful career in the field of Data Science.