Top 6 Benefits of Learning Data Science with Python - Over the last decade, a new requirement has emerged in the industry that has taken the world by storm and has completely revamped our thinking...
This requirement is none other than that of Data Scientists. Data Scientist is one of the hottest requirements in the job market. One of the main reasons for this widespread popularity is that data analytics can find use in all industries. Its use is not limited to just the software or IT industry. It has found application in industries such as intelligence and security, healthcare, business, government, energy, and much more. This article will not only give you reasons on why you need to learn data science, but it will also tell you why learning data science with Python training is the better option.
Why Learn Data Science?
Data analytics is all about solving problems. It involves looking at the data you have and using it to solve a problem that you are either facing currently or you anticipate you will have to face in the future. One of the main advantages of studying data science is that you can work in the field you like. Every industry has its own unique set of present and future problems and data science is the way to solve them. This is why every industry is currently looking for data scientists and you can have your pick among them. You will not get this option with any other course.
Data Science is not just the current trend, it is also the future. When you are planning your career, it is important to consider the present as well as future requirements. Currently, there is a shortage of data scientists. Companies are looking to hire more people in this post but they are unable to find qualified candidates. Studying data science or data analytics right now will put you on the path of some very lucrative career choices.
Why learn Data Science with Python Training?
While there are many different ways to implement data analytics, Python has become very popular and rightfully so. Python is a powerful language that is easy to learn and implement. Here is why you should learn data science with Python training.
1. Ease of Learning
Python is one of the easiest languages to learn. Even if you have no background with coding, learning Python will not be difficult. One of the main things that hold people back when they hear about becoming a data scientist is the lack of coding skills and the perceived difficulty in learning the same. You won’t face this problem with Python.
2. Faster Development and Processing
While dealing with huge amounts of data, speed is key. A slow language can slow things down incredibly. Python is a clean, easy to handle language that requires only a few lines of coding. This significantly cuts down on the coding time required. Python’s slow execution was one of the reasons that held it back from being fully accepted. However, since the introduction of the Anaconda platform, even this complaint has been dealt with.
3. Powerful Packages
Python also comes with huge range packages such as NumPy, SciPy, PyBrain, Pandas, etc. that makes it incredibly simple to code complex data analytics problems. There are also many libraries that support the integration of Python with other languages such as C and SQL. These further aid Python in making it more powerful.
4. Community Support
One thing that makes Python is easy to learn and understand is its strong community. Any time you get stuck with any problem, you can ask the community and they will always help you. In addition to this, many in the community are also constantly developing new packages and libraries for a variety of uses. With the popularity of Python for data science increasing, many of these are being developed for the use of data scientists.
5. Better Data Visualisation
Visualization is key for data scientists as it helps them understand the data better. With libraries such as ggplot, Matplotlib, NetworkX, etc. and APIs such as Plotly, Python can help you create stunning visualizations. You can also integrate other big data visualization tools in Python. All of this adds to Python’s usefulness for a data scientist.
6. Compatible with Hadoop
One of the most popular open source platforms for big data, Hadoop is inherently compatible with Python. The Python package known as PyDoop lets you access the API for Hadoop. This lets you write Hadoop programs using Python. The package also lets you write code for complex problem solving with little effort.
Kickstart Your Career
If you are at the start of your professional journey and are thinking about which path to take, then you should definitely consider going for data science with Python course. This is one of the most sought after career options that can set you on the fast track for a very high paying and exciting profession.
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This Edureka video on 'Python For Data Science - How to use Data Science with Python - Data Science using Python ' will help you understand how we can use python for data science along with various use cases. What is Data Science? Why Python? Python Libraries For Data Science. Roadmap To Data Science With Python. Data Science Jobs and Salary Trends
An overview of using Python for data science including Numpy, Scipy, pandas, Scikit-Learn, XGBoost, TensorFlow and Keras.