DEV Community

loading...
Cover image for Learning Path- How to expand Your Python Skills

Learning Path- How to expand Your Python Skills

Kat Holder
“ In order to be irreplaceable, one must always be different”
・4 min read

Python is one of the versatile, dynamic, and easiest languages in the programming world. It easily runs in different applications. It has huge support from the community which makes it an ever-evolving language in the programming world. Now, the thing is that even if the language is easy, it takes practice and devoted time to master it at the same time. After you have learned the basics of python, it is important to make sure your learning curve does not flatten in this language.
In order to strengthen your solid knowledge base, let’s look into some of the great places where you can polish your hold on this language.

Python Beginners Guide For Learning

1. TalkPython Training
It is a course that teaches Python by giving you practice assignments on building projects. You use the syntax of Python to do your projects in Python. You can purchase the course for $69 for lifetime access. The name of the course is Python Jumpstart by building 10 Apps.
The structure of this online training is dynamic. There are podcasts- Talk Python To Me. Podcast mapping the new things that are registering in the Python world to free office hours where you can drop in on a group of students and discuss your course and your intakes with fellow students.

2. Programiz
This one is best for beginners as the tutorials are easy to understand and learn. It uses examples for each concept to make your understanding clear. Along with that, it provides an online interpreter to work with Python.Check this Article For the Best Python Projects For Beginners
The modules of this course are broken into small chapters that explain the concepts in a fast yet succinct way.

3.Automation
Written by Al Sweigart, who teaches programming to both kids and adults. This book has received rave reviews as it teaches the boring stuff of Python in a fun way! Highly acclaimed, it helps you understand the concepts of Python using practical examples. It is easily available on Amazon.)

4. Lists and for loop Practices
At Dataquest, Python is made fun when you are asked to solve or write codes by giving baby steps to teach you how to code in Python first, and then when you move to upper levels, it asks you to think and write the code all by yourself.

Lists - List can be compared to arrays in other languages. In Python, it is a type of container in Data Structures, that stores multiple data at one time. In python, lists are ordered and have a specific count.

Loops - There are three ways through which Python executes loops in the code. However, they differ in syntax and condition checking time. Though it has similar basic functionality, taking this tutorial will help you how they differ and their inbuilt intricacies.

5.Cleaning and Preparing Data in Python
As a data scientist, you will realize that all the data is not clean and you would often require a process to prepare that will be called data cleaning. This one will help you figure out how to do it.

For Advanced Learning

6. NumPy index selection
Numpy comes into play when you have to perform operations on all elements of two lists directly. Otherwise, an error pops up. You use an array to index a Numpy. The best part- they can be indexed with other arrays as well.

7. Boolean indexing with Numpy
It is a type of indexing that uses actual values of the data in the Data Frame. You can filter it through four ways.

8. Ndarray methods
An array in Numpy is a table of elements which are numbers of the same type to be indexed by a tuple of positive integers. An array class in Numpy is defined as ndarray.

9. Selecting data in a data frame
A data frame is a two-dimensional data structure where data is in a tabular form. You can perform basic functions like selecting, deleting, editing, and renaming.

10. Line graphs with Matplolib
Matplotlib is a data visualization library in python. Since it has become important to analyze data in the world of data scientists, it comes in pretty useful. There is this pyplot- a sub-library where it has a collection of functions that help in creating a variety of charts.

11. Aggravating data in Python
This is done using the pandas and NumPy libraries. The aggregation takes place when the data gets converted to a data frame.

Wrapping Up

Other websites also provide a detailed discussion on what type of topics to pick up when you are in the beginning stage. It just requires patience and perseverance. One can learn Python in a month and get things done but mastery is a skill that is sought after in the industry. Taking one step at a time will help you expand those skills and you can go for big projects that are both rewarding and challenging.

Discussion (0)