Learn Data Science with Python Course Online in 2021

09-Jan-2021

What is Python?

Python is a high-level programming language. High-level means that it has many built-in data structures and other facilities which differentiate it from low-level languages such as assembly languages or machine code languages. It has a very sparse and minimized amount of syntax, and uses whitespace for formatting. This means that Python code is not verbose at all and very easy to read.

It also has dynamic binding and dynamic typing, which makes programming in it a very pleasant and smooth experience. It is usually used for Rapid Application Development or RAD – creating prototypes, testing concepts, and creating simulations quickly. It is also used frequently as a glue language or a scripting language to join together or connect existing components of an application.

It also comes with a very comprehensive collection of libraries which make it easy to write complex programs without having to reinvent the wheel for every little function. In addition to its prepackaged libraries it also has many community-made libraries available for use. It has a very large community which has members from many fields such as computer science, mathematics, statistics, information technology, information security, data science, Game development, medicine and pharmocology, and even biology and bioinformatics. Many individuals opt for data science certification courses in order to learn Python as it is an integral part of data science.

👉  Why is Python Significant for Data Science?

Why is Python Popular?

Python has many features which make it very attractive for programmers of all kinds. In fact, it is the fastest growing programming language in the world and several websites predict that it will become the most popular programming language within the present decade. Some reasons why Python is so popular are -

• Python is a very accessible language. It has a very simple syntax which is easy to read and emphasizes natural thinking and natural language-like characteristics over complex verbosity. Thus it is a language which newcomers and even beginners to programming find very easy to learn.

• Python has support from big corporate sponsors. Facebook, Amazon Web Services, and especially Google have provided a lot of support to the worldwide Python community and the official Python maintainers. Resources such as programmers, tools, bug fixing marathons, and even money have been spent by these sponsors to improve Python and help it advance and grow. This official corporate backing has attracted a lot of programmers to the language. They even offer data science certification training for all kinds of learners.

• There are a huge number of Python libraries and frameworks available. This is mostly due to the huge and supportive community which has flocked around the Python programming language. It is also due to corporate sponsorship and backing, since large companies drive efforts to create new and well-designed libraries and frameworks which solve common problems faced by programmers around the world. All these libraries and frameworks are usually introduced to learners in any data science training.

How do you learn Python?

• The first step is to code. As you read a book, or study from an online tutorial, or even take a certification course, you should keep implementing the concepts you learn in real code. Write programs to solve small problems everyday. Reread your code and review it to see if you can improve it in terms of readability, efficiency, or elegance.

• Make copious notes about everything you learn and revise them from time to time. By taking notes by hand you will be able to retain more information about Python for a longer period of time. You should note down all the miscellaneous details which you think are important or anything which seems like an interesting or noteworthy feature in the language. These details may seem small and minor at first, but over time you will have collected a lot of information which is important but not obvious at first sight.

• Python is an interpreted language. So the Python installation comes bundled with an interpreter by default. A learner of Python should make full use of the interpreter to develop their programs interactively. He should test different components of the program by sending different inputs to it after loading it in the interpreter. This will help him develop an intimate understanding of the basic concepts of the Python programming language.

• Enroll in a data science certification course. Most of these courses are very focused on Python as Python is required in most data science tasks.

Careerera’s Data Science with Python course -

Careerera offers a very excellently designed data science certification course, the title of which is ‘Data Science with Python.’ This course has been designed with the most ideal learning objectives in mind. After taking this course, you will be able to -

• Download and run various analysis algorithms on data with the help of Python programs.

• Learn Python programming techniques to analyze and evaluate different kinds of data – ordinal, categorical, and encoding.

• Produce data visualizations such as scatter plots, polar area diagrams, time series sequences, line graphs, timelines, line graphs, tree diagrams, ring charts, sunburst diagrams, matrix charts, node link diagrams, word clouds, alluvial diagrams, scatter plots, pie charts, venn diagrams, stacked bar graphs, histograms, flow maps, density maps, cartograms, heat maps etc.

• Present the results of your data analysis step by step with the help of the full set of features of the IPython notebooks.

• Use data science tools and techniques to carry out predictive modeling.

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