Online kurs: Analyzing Data with Python

10 jun

Analyzing Data with Python -

Nowadays huge amounts of data are created every day and being able to analyze these and make use of them means a lot today, not to say more. Those who are skilled to carry out analysis, manipulate and even use data are in great demand these days. In case you have started using Python and are interested in data analysis, then joining this course advised by will surely be of interest to you.

About this course

Data Scientist’s job is worthwhile because it not only gives you a chance to earn much money, but through it you can even have your contribution in the solution of the world’s most important issues. This course is aimed at those who are ready to jump into the world of data and already have some experience in using Python. It will guide you through several stages starting with the core concepts of Python and getting to the research of multiple data types. The course includes lecture materials and a variety of practical tasks.

Covering this course will enable you to do data preparation, elementary statistical analysis, generate amazing visualizations of data and make some predictions. You will be familiarized with a variety of libraries and some of the algorithms of machine learning and many more.

What you’ll learn

This course is a good chance to learn to deal with data effectively. Once you do it, you will be able:

  • To manipulate data through performing various operations with them.
  • To employ SciPy labs, Pandas and Numpy working with sets of data.
  • To deal with several open-source libraries.
  • To shape models of machine-learning and predict using its algorithms.

Join the course

This 5 module course of Analyzing Data with Python should be covered in 5 weeks, but you are free to choose your own pace. It represents a good combination of theory with practice to let you start working on your own once you have completed it. Join now and you will be one step closer to your goal of becoming a data analyst.

More information you can find on the link

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