Python For Data Science with Basic To Advanced Concepts

by Akash Raj | 2023/01/30 | Data Science

Do you want to build a secure career with continuous growth? Learn Python for data science and you will. Python is one of the most used programming languages worldwide. Python is simple to master, and once you do, you can use those skills to find a fantastic job in the quickly growing data science sector. There are thousands of platforms providing a python Course but where to put our trust is a difficult decision. 

Python in a nutshell

Programming languages like Python are robust, flexible, and frequently used. Python programming is used in cutting-edge software industry technology such as web development, machine learning applications, and other fields. When compared to other programming languages like C++ and Java, Python is a great choice for beginners as well as seasoned professionals. 

Insights on the Python programming language are provided below:

• The most widely used high-level, versatile programming language at the moment is Python.
• Python supports procedural and object-oriented programming paradigms.
• Compared to other programming languages like Java, Python programs are typically smaller. Since the language requires indentation, programmers have to type considerably less, and their work is always readable.
• Google, Amazon, Facebook, Instagram, Dropbox, Uber, and many other tech giants employ the Python programming language.
• Python’s vast standard library is its greatest strength.

As already said, there are so many platforms who are selling varieties of modules in the name of python courses . To pick the right python course is tough for a layman. In this blog, you will find all the important topics that must be covered in a python course for data science.

Topics that must be covered in any python for data science bootcamp

Type casting and strings

As a developer, you could run into a variety of circumstances when you need to transform one data type into another. Casting numbers into a string and casting strings into numbers are two examples. Python has tools that can make this process easier and streamline your workflow. Every developer will find typecasting to be a useful ability at some time in their career. 

Python loops

Using a loop command, we can repeatedly run a single statement or a collection of statements. Python offers the following loops to satisfy your looping requirements. Python offers three methods for carrying out the loops. Although the syntax and the length of time needed to check the condition vary, all of the strategies have the same basic functionality.

The Python programming language provides the subsequent categories of loops.

While loop: Repeats a sentence or set of sentences as long as the condition is true. Prior to starting the body of the loop, the condition is tested.

For loop: This kind of loop condenses the code that controls the loop variable and repeats a code block several times.

Nested loop: This allows for loops inside loops to be iterated.

Loops are a useful tool when working with data in Python. But when you first start out, they might also be a little bit confusing. 

Data structures

Data structures are a means to arrange data such that, depending on the circumstance, it can be retrieved more effectively. Any programming language’s foundational building block upon which a programme is based is the data structure. The fundamentals of these data structures are simpler to master in Python than they are in other programming languages.

An ideal python course should talk about Python’s data structures and how they connect to some of the language’s unique data types. In-built data structures, such as list tuples, dictionaries, etc., as well as some sophisticated data structures, such as trees and graphs, should also be covered.

File handling in python

We use files to temporarily and permanently store data. A file is a grouping of data that is kept on a disc and is referred to by its filename. File operations like opening, reading from, writing into, closing, renaming, deleting, and numerous file methods are very important.

Exception handling in python

The two forms of errors in Python are exceptions and syntax errors. When internal circumstances take place that alter the program’s usual course, exceptions are raised. The use of the try, except, and finally statements to manage exceptions in Python must also be covered in a python course with the aid of suitable examples.

REGEX

A Regular Expression (RegEx) is a special jumble of characters used to locate a string or collection of strings. By comparing a text to a specific pattern, it may determine if it is present or absent. It can also divide a pattern into one or more sub-patterns. Regex functionality is available in Python through the re module. Its main purpose is to provide a search, for which a string and a regular expression are required. It either returns the first match in this case or none at all. 

Numpy

Working with multidimensional arrays and matrices is made possible by the Python package NumPy. Because it is quick and effective, it is ideal for calculations in science or mathematics. The linear algebra and signal processing operations are also supported by NumPy. NumPy is therefore likely the library for you if you need to perform any mathematical operations on your data.

Pandas

Data analysis necessitates extensive processing, including cleansing, merging, and other operations. For quick data processing, a variety of tools are available. For this, a lot of people favour using Pandas because they are quicker, easier, and more expressive than other tools. Pandas is an open-source package that provides Python users with high-performance data manipulation. Because Pandas is built on top of the Numpy package, Numpy is necessary in order to use Pandas. 

The best content: CloudyML python online course

CloudyML has built a detailed quality rich python course. CloudyML is one of the top online data science learning platforms. It offers the most affordable and quality rich data science learning courses. One of these courses is the python course. This python language course by CloudyML covers all important aspects that were discussed earlier in this blog. The python course by CloudyML can help you secure a successful career. After reading this blog, you can also compare other courses as well.

Why Opt for the CloudyML Python Course?

At CloudyML, the very first principle we bring in our process is to come up with affordable quality education. The python course duration and fee at CloudyML is extremely affordable in comparison to the market price. The whole python course in addition with many other data science subjects like SQL, tableau, excel and much more in just Rs. 10000. In addition to all the topics that we discussed earlier, there are many other important concepts like functions, matplotlib, seaborn etc. that are discussed in detail in this course. The CloudyML python course also covers various case studies like Black Friday case study, Hangman project and Haberman cancer survival data analysis. 

Shocked!!! Give a minute to come back to your senses and sink this in. 

With world-class educators, CloudyML comes with a very simplified and quality-rich curriculum at a very nominal price of just Rs. 10000. 

Justifying CloudyML python programming course fees

CloudyML contains the highest quality of course content and the most affordable prices. CloudyML believes in giving value for every penny. CloudyML provides self-paced courses with a learn-by-doing concept. To learn data science at CloudyML means bringing your hands to practise side by side. The purpose is to bring the students to the level of cracking any data science/analytics interview from scratch.

An in-depth study of python programming classes with the help of

• Guided assignments 
• Real-world projects
• 1-1 teaching assistant
• Daily doubt-clearing support

Hands-on practice and the guided approach make the courses a must to opt for.