The benefit of getting familiar with Data Science Concepts

There are several benefits of getting familiar Data Science concepts. Here, I will list the most obvious:

• You will have another methodology in your portfolio of tools for conducting research.
• The certifications that you will obtain will be part of your CV and will be able to differentiate your profile.
• If you plan a a programming intensive and prototype driven approach for conducting your thesis (or research in general) you will be able to focus on the most interesting aspect from day one. This will prevent the unfortunate situation where you will be spending your time in catching up with your programming skills instead of really conducting research.

Courses Related to Data Science In DataCamp

This is a Python 101 course to perform Data Science:

• https://app.datacamp.com/learn/courses/introduction-to-data-science-in-python

This course is a bit more advanced compared to the previous one and focuses on Python specifically for data science:

• https://app.datacamp.com/learn/courses/intro-to-python-for-data-science

Here you learn to write your own custom functions, complete with multiple parameters and multiple return values, along with default arguments and variable-length arguments:

• https://app.datacamp.com/learn/courses/python-data-science-toolbox-part-1

This one complements the previous one and lets you practice doing a case study:

• https://app.datacamp.com/learn/courses/python-data-science-toolbox-part-2

With this you will learn how to improve the efficiency and readability of your code:

• https://app.datacamp.com/learn/courses/writing-efficient-python-code

And this one provides you with techniques for data cleaning and data (pre)elaboration:

• https://app.datacamp.com/learn/courses/cleaning-data-in-python

Finally, the following 2 courses will let you familiarize yourself with Tensorflow

• https://www.datacamp.com/tutorial/tensorflow-tutorial
• https://app.datacamp.com/learn/courses/introduction-to-tensorflow-in-python

If you like the idea of learning Data Science, consider sharing and spreading the voice:

A collection of #courses in DataCamp for getting familiar with #DataScience concepts using #Python . They are free if you are a #student. #DataScientist #pythonprogramming
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Bonus Course (in OOP):

This course is not strictly related to Data Science skills. However, the more the complexity of your code will grow the more you will need to organize it properly. If you are not familiar with OOP at all, this post is a good introduction to Object Oriented Programming.

• https://app.datacamp.com/learn/courses/object-oriented-programming-in-python

The post Using DataCamp for getting familiar with Data Science concepts appeared first on Francesco Lelli.

• After the initial pain, and maybe a bit of a slow start, your thesis will advance ten times faster and you will be capable to achieve more than you can imagine.
• What you will be learning will not be lost. Many companies use a similar environment (if not the same).
• Many of these resources are free and you will be able to use them for other projects after the end of this academic endeavor.

In other words, you have nothing to lose. All you have to do is to endure a bit of the initial annoyance that is required for a proper warm up of your programming environment. However, the reward is much greater than the initial investment.

In this article, I list only a very few resources and only the ones that are free. In the internet you can find many more.

Programming skills: no matter how much you know, there is always room for knowing more. Most libraries, both public and university, have free subscriptions to courses. For example, the library in my university gives free access to DataCamp to all the students that request it.

If you are not familiar with the platform, it contains a set of courses at all levels and many of them have code examples. As they cover a large range of cases, some of them will be relevant for your thesis. All you have to do is to dig into the list and familiarize with the code that is most promising for the work that you plan to do with your supervisor.

Get a student account in GitHub, it is a free repository that you can use for storing your code. Calming student status will grant you a pro version for free as well as many discounts for products of other companies. In addition, you will also not loose these perks after the graduation – some of them could be useful for you in the future.

Get an account in Kaggle, again, it is a free service that has courses and datasets. They also offer a web based programming environment with the idea that if you will find yourself in need of additional computation, you will use their services. As a general rule, I would recommend to have a local working environment instead of a cloud based like the one of Kaggle. However, a cloud based environment may be useful under certain conditions.

Set up Anaconda (or Eclipse) in your laptop. An Integrated Development Environment is extremely useful when you have to do some professional programming. Anaconda is free, open source and perfect for Python. Eclipse is its counterpart for Java. In the article below you can read about some of the benefits of an IDE. Once you will start using one you will never go back:

This article is a mini-tutorial on how to set up the environment for Anaconda:

Finally, in the article below, you can familiarize with the debug functionality. It is one of the most useful features of an IDE and can really save you a tremendous amount of time:

I would strongly encourage you in enduring the pain of getting familiar with the tools and the resources that I shared with you in this article. In the long run your future self will be extremely thankful.

A working environment is a very personal thing and I can imagine that every supervisor has their own. Consequently, I would encourage you to discuss the details during your first meeting. At the same time, I can imagine that these tools will be, in a way or an other, useful for your future work. In addition, the fact that you will have your working environment ready will allow you to advance conversations that are more specific to your thesis and you will result in a better use of the (limited) time that you will share with your supervisor.

#free #Resources that will #SHARP your #programming #environnement. #Java #pythonprogramming #pythoncode #DataScience #DataAnalytics #data
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By the way, here you can fine my profiles in GitHub Kaggle and DataCamp:

• https://github.com/Nym77
• https://kaggle.com/francescolelli
• https://www.datacamp.com/profile/flelli
• https://www.freecodecamp.org/francesco-lelli

Are you really committed in improving your programming skills?

Free Code Camp is an open source free course that will guide you in a project based journey towards advanced programming skills. It contains also a session on how to pass a programming oriented job interview.

Introduction to Computer Science from Harvard This is a free edX course from Harvard. You can also get a certificate but this will cost you something. Nevertheless the entire course is free.

Something else:

This article (Free Resources That Will Warm Up Your Programming Environment) is part of the miniseries on how to do a good thesis, you can see the full list of post at the following link:

This article is also part of a miniseries on how to become a better programmer. You can see the full list of posts at the following link:

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