How To Achieve Proficiency in Data Science Using Python in Nepal

Data Science is a constantly flourishing branch of study in Information Technology (IT) that mainly focuses on data collecting, processing, and formulation of numerous relevant analyses and judgments to support corporate success. It engineers the professional in data presentation skills and thrives on the in-depth concepts of spreadsheets. The main question over here is why it is mandatory to learn Data Science using python. 

Some of the popular and commonly used python libraries to manage the applications of data science and ML (Machine Learning) are Pandas, NumPy, Matplotlib, SciPy, and Scikit-learn. Python's simplicity of use and straightforward syntax is further strong reasons to employ it in a data science course. As a result, even those with no prior knowledge can easily pick it up. Additionally, it expedites the development of programs and prototypes.

Last but not least, using Python and data science makes it simpler to gather, comprehend, analyze, and extract value from data. 

Most Commonly Used Libraries for Data Science

Although working with data in plain vanilla Python is doable, there are several open-source tools that make working with data in Python a lot simpler.

There might be a useful library you're overlooking. The most significant Python ecosystem libraries for data science activities are listed below, including topics like data processing, modeling, and visualization.

Data Mining

• BeautifulSoup
• Scrapy

Data Processing and Modeling

• Pandas
• NumPy
• SciPy
• XGBoost
• SciKit-Learn
• Keras
• TensorFlow
• PyTorch

Data Visualization

• pydot
• Bokeh
• Matplotlib
• Plotly
• Seaborn

Features of python language

There are many features of python, some of them are mentioned herein:

• Simple and Easy to Learn

When compared to other programming languages, Python is simple to learn. Its syntax is straightforward and closely mimics that of English. The indentation identifies the code block; neither the semicolon nor the curly brackets are used.

• Free and open source

Python is open source and it is freely available for everyone. You can download it from its official website python.org. Although you can download, you can create your own modules or libraries and share them.

• GUI Programming Support

Graphical User Interface(GUI) is used for developing Desktop applications. Python has many GUI libraries like PyQt, Tkinter, Kivy, Pyside, etc. It has the feature to make graphics-intensive software easy and fast. GUI enables users to interact with systems and applications more easily.

• Object-Oriented Language

Python supports object-oriented languages, as well as the concepts of classes, object encapsulation, and the creation of objects. It supports inheritance, polymorphism, encapsulation, etc. The concept of object-oriented programming (OOP) is focused on creating reused code. Creating objects to solve the issue is a common strategy.

• High-Level Language

Python is a high-level language. It is an interpreted dynamic language that must be operated in the supplied system utilizing another program rather than its native processor. It is not a typical straight compiled language like Java or C. The architecture, memory management, or underlying machine type need not be considered by the developer while writing code.

While there are many additional features, earlier mentioned are the most important.

What Do Data Scientists Actually Do?

If you ask a same questions to five different data scientist, there is high chance of getting different answer. This is due to the fact that a data scientist's responsibilities and duties vary substantially based on a variety of variables, such as experience, industry, and the size of the employer. The primary responsibility of a data scientist is to gather, purify, and analyze data in order to derive insightful business knowledge that can be applied to better business decision-making. Gathering and processing consumer and market data, creating infrastructure to store and organize acquired information, and clearly presenting studies to firm decision-makers are just a few of their typical duties. Regardless of your function, there are certain skills you'll need to be adept in if you're considering a career as a data scientist.

Some required technical skills for data scientists are mentioned below:

• Programming
• Machine Learning
• Data Visualization
• Deep Learning
• Processing large data sets
• Statistical analysis and computing
• Data Wrangling

Data science careers are not just for those with technical skills. Together with other developers, engineers, analysts, coders, and business managers, you'll work on teams. These practical abilities will help you advance:

• Storytelling
• Communication skills
• Logic and critical thinking
• Business sense

Although technology is still in its early stages in Nepal, it has not yet acquired high-profile IT designations. In Nepal, there is a significant demand for work as data scientists, however, compared to other IT positions, there is a shortage of qualified candidates.

It is anticipated that there will be a significant increase in the number of job opportunities for data scientists in the near future. Though it will be a futuristic choice to become a data scientist.

Benefits of Data Science with Python Training in Nepal

For IT professionals who prefer to build their career in data analytics, this Data Science course is helpful. The Data Science with Python course will improve both your awareness of data science and your proficiency with Python-based analytics. You'll learn the fundamentals of Python programming after completing this course, and you'll also have a greater understanding of data analytics, data visualization, machine learning, natural language processing, and web scraping. Additionally, this program will help you with the below-mentioned benefits:

•  develop your skills in machine learning
•  gain a thorough understanding of data science procedures
•  learn key Python programming ideas
•  extract data from different websites
•  perform data analysis, as well as many other skills.

Python's ease of use and straightforward syntax make it simple for people without engineering backgrounds to adapt, which is one of the key reasons why it is so popular in the scientific and research fields. Additionally, it works better for quick prototyping.

As per the global job market, there is high demand for the professionals falls on different designation of Data science field. Recent trends suggest us that the scope of Data Science is unlikely to change in term of futuristic analysis. Do you want to initiate your career in the field of Information Technology (IT)? Data Science would be the best career option to you. One of the determinant factor responsible for the growth pace of your career is the institute you chosen. So, TechAxis is here to assist you along your career in Data Science with Python certification course since long time. If you have any queries regarding the course (Data Science and related IT courses), feel free to write us.