ACTE's python online training course make you master the ideas and gain in-depth expertise on writing python code and packages like SciPy, Matplotlib, Pandas, Scikit-Learn, NumPy, internet scraping libraries, Lambda function moreover you'll find how to write code for large knowledge systems like Hadoop & spark. The whole online course content is intended by business professionals to induce the most effective jobs within the high MNCs. As a part of this coaching, you may be engaged on real-time projects and assignments that have large implications within the real world business situation so serving to you way your career effortlessly.
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R and Python are the two most popular programming languages used by data analysts and data scientists. Both are free and open source - R for statistical analysis and Python as a general-purpose programming language. ... Knowing both R and Python will open doors for more job opportunities.
We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings for Data Science With Python. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.
- SciPy
- Pandas
- Matplotlib
- NumPy
- SciKit
- Seaborn
Before proceeding with this tutorial, you should have a basic knowledge of writing code in Python programming language, using any python IDE and execution of Python programs. If you are completely new to python then please refer our Python tutorial to get a sound understanding of the language.
Yes, If you have basic knowledge, you can learn it online but you need good practice , projects and case study. ... You can start learning R and Python. There are many free cources available to start with. Down the line when you learn this , you will understand how comfortable you are with learning programming.
Our course ware is designed to give a hands-on approach to the students in Data Science With Python. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
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- Python for data science course duration is short and within 2-3 months of pursuing this course you can gain the confidence of making or attempting small projects.
- There are a lot of estimates for the time it takes to learn Python. For data science specifically, estimates a range from 3 months to a year of consistent practice
- Talking about how long it will be there in market no one can actually answer it precisely.
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There is a shortage of data scientist at all the levels from beginner,Freshers to that of manager level.Since IT industry is at the verge of change so many middle level manager s and professional across domains are finding their career growth stagnant .Data science is the best option to overcome downturns of career stagnation.
Annual pay hikes for Analytics professionals in India is on an average 50% more than other IT professionals.Salary trendsfor Data science professionals across the globe indicates a positive and exponential growth.
Why Python is the Best
Python has long been known as a simple programming language to pick up, from a syntax point of view, anyway. Python also has an active community with a vast selection of libraries and resources. You have a programming platform that makes sense to use with emerging technologies like machine learning and data science.
Professionals working with data science applications don’t want to be bogged down with complicated programming requirements. They want to use programming languages like Python and Ruby to perform tasks hassle-free.
- Ruby is excellent for performing tasks such as data cleaning and data munging, along with other data pre-processing tasks. However, it doesn’t feature as many machine learning libraries as Python.
- This gives Python the edge when it comes to data science and machine learning.
- Python also enables developers to roll out programs and get prototypes running, making the development process much faster. Once a project is on its way to becoming an analytical tool or application, it can be ported to more sophisticated languages such as Java or C if necessary.
- Newer data scientists gravitate toward Python because of its ease of use, which makes it accessible. So popular in fact, a staggering 48 percent of data scientists with five or fewer years experience rated Python their preferred programming language.
- This number tapers off as the experience level increases and the analytics become more intensive. Python has proven itself to be an excellent starting point for data scientists.
Why is Python for data science preferred
- In many scenarios, Python is the programming language of choice for the daily tasks that data scientists tackle, and is one of the top data science tools used across industries.
- For data scientists who need to incorporate statistical code into production databases or integrate data with web-based applications, Python is often the ideal choice. It is also ideal for implementing algorithms, which is something that data scientists need to do often.
- There are also Python packages that are specifically tailored for certain functions, including pandas, NumPy, and SciPy. Data scientists working on various machine learning tasks find that Python’s scikit-learn is a useful and valuable tool.
- Matplotlib, another one of Python’s packages, is also a perfect solution for data science projects that require graphics and other visuals.
- It is called ‘Pythonic’ when the code is written in a fluent and natural style. Apart from that, Python is also known for other features that have captured the imaginations of data science community.
Why is Python important for Data Analysis?
It's Flexible
If you want to try something creative that’s never done before; then Python is perfect for you. It’s ideal for developers who want to script applications and websites.
It's Easy to Learn
Focus on simplicity and readability, it boasts a gradual and relatively low learning curve. This ease of learning makes Python an ideal tool for beginning programmers. Python offers programmers the advantage of using fewer lines of code to accomplish tasks than one needs when using older languages. In other words, you spend more time playing with it and less time dealing with code.
It's Open Source
Python is open-source, which means it’s free and uses a community-based model for development. Python is designed to run on Windows and Linux environments. Also, it can easily be ported to multiple platforms. There are many open-source Python libraries such as Data manipulation, Data Visualization, Statistics, Mathematics, Machine Learning, and Natural Language Processing, to name just a few (though see below for more about this).
It’s Well-Supported
Anything that can go wrong will go wrong, and if you're using something that you didn’t need to pay for, getting help can be quite a challenge. Fortunately, Python has a large following and is heavily used in academic and industrial circles, which means that there are plenty of useful analytics libraries available. Python users needing help can always turn to Stack Overflow, mailing lists, and user-contributed code and documentation. And the more popular Python becomes, the more users will contribute information on their user experience, and that means more support material is available at no cost. This creates a self-perpetuating spiral of acceptance by a growing number of data analysts and data scientists. No wonder Python’s popularity is increasing!
