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Python for Data Science: From the Basics to Advanced

This free online course will teach you the basics of python programming for data science and then NumPy and Pandas.

Publisher: Ermin Dedic
Python is one of the best and fastest-growing programming languages used in data analysis worldwide. This free online Python for data science course will teach you how to apply the fundamental programming concepts of Python such as looping, variables, data types and data structures to data science. This course also explores the NumPy and Pandas Python libraries that will help you further manipulate, analyze and visualize data.
Python for Data Science: From the Basics to Advanced
  • Duration

    6-10 Hours
  • Students

    579
  • Accreditation

    CPD

Description

Modules

Outcome

Certification

View course modules

Description

The demand for skilled data scientists is increasing exponentially and being a data scientist requires sound knowledge of programming languages. Python is one of the best data science programming languages. Apart from being very easy to learn and implement, it has a wide range of applications in web development, game development and more. This course will teach you programming concepts in Python and how they can be applied to manipulate and analyze data. The course begins by introducing you to the Jupyter Notebook environment where you will be writing your code. Moving on from there, you will be taught how to use markdown cells to add images, text and links to your code. You will learn about variables, indentation and how to comment on your code for other programmers to understand. Furthermore, the course will show you how to work with different data types in Python such as lists, dictionaries, sets, tuples as well as how to use operators.

Next, the course explores the various decision-making statements in Python such as the 'if statements', 'else statements', the 'else-if statements' as well as the 'for loops' and the 'while loops'. Functions are a great way to save time and effort when writing computer programs. This is because they are a set of instructions that can be used repeatedly to perform a specific task when called upon. In this course, you will create a function that converts the temperature scale from degree Celsius to Fahrenheit and then call it out to execution. Learners will gain an understanding of the difference between the print function and the return statements as well as the lambda keyword and its syntax. Upon that, this Python course will teach you how to iterate and use the concept of nesting to access other functions and variables. You will learn about double indexing and how to select a specific item from a list or dictionary. 

Python libraries play a very important role in data science as they help eliminate the need for writing programs from scratch. The final part of the course will focus on two key Python libraries (NumPy and Pandas), which ease out sorting, manipulating and the analysis of a data set. This Python course will teach you how to create and shape an array using NumPy and how to select items from a data set using the NumPy indexing and NumPy slicing techniques. The various functions of NumPy which serve different purposes will be reviewed in this course. Thereafter, the course will focus on pandas where you will gain a thorough understanding of how to engineer and examine raw data. Do you wish to become proficient in developing programs using Python? Are you seeking to become an expert in data science? Then this course is your stepping stone to a career in data science, as the course walks you through the basics of the application of Python to data science to advancement. A computer and an internet connection are all you need to get started. So why wait? Start this course now.

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