Python is not just a programming language used for web and app development, but also it has found importance in Data Science, Machine Learning, Artificial Intelligence, task automation, data analysis, data visualisation, and in multiple other fields.
Python developers have been in demand for several years, and recently, Python ranked among the top five most demanded programming languages globally. The best part of Python programming is that anyone with basic computer knowledge can learn and use it.
The first section of the course introduces learners to Python programming, including the process of downloading and setting up its environment, and Python IDEs. Plus, you will know where Python is mostly used and why it is gaining popularity in Data Science.
Subjects covered in introduction and setting up the Python environment:
Once you have installed Python on PCs and Macs, you must know how to write a program. But before that, this course will introduce you to the basic syntax, input and output operations, comments, variables, data types, and typecasting in Python. While variables store data of multiple types, each type has a different function. You will learn each data type category and cast them from one type to another.
Operators in a programming language instruct the machine to perform a particular operation on variables and values. Python operators are of multiple types, and each defines a unique operation. For example, the arithmetic operator “+” instructs the interpreter to perform “addition”. In this part of the course, you will be introduced to each of these operators and will understand where to use them and how they function in an instruction.
Strings are usually the collection of alphabets, words, or characters. These are some of the primitive data structures and building blocks for data manipulation. This part of the Python course will introduce you to strings and their representation, multiple string methods, string indexing and slicing, and formatting strings.
Python programmers use lists to store multiple items in a single variable. Lists are one of the four main in-built Python data types, and you can identify them when mentioned within square brackets. List items maintain an order, are changeable, and allow duplicate values. This section will cover the basics of creating Python lists, including list indexing and slicing, and different list methods.
Another in-built Python data type, other than lists, is tuples and it also stores multiple items in a single variable. Python tuple items are written within round brackets, and these collections maintain an order and are unchangeable. This part of the Python course will give in-depth knowledge of tuples, including their syntax, properties, indexing and slicing, and tuple methods.
Just like Lists and Tuples, Sets form an essential part of Python’s in-built data types that can store several items in a single variable. These elements are written within curly brackets and are unordered, unchangeable, and unindexed. Sets are different from the previous two data types, and learners will know the difference in this section. Plus, you will learn the syntax for creating sets, their operations and methods, and updating sets.
Lastly, you will know dictionaries, one of the four in-built Python data types used to store data values in a key:value pairs, and are written within curly brackets. This section will introduce you to the creation of dictionaries and storing data within them, along with knowledge of keys and values, ways to access elements of dictionaries, and different dictionary methods.
While you are creating a Python program, you may need to put some conditions. For example, if a condition is true, then the next statement will be executed; otherwise, another statement will be printed. Python conditional statements consist of if statements, if-else statements, and if-elif-else statements. This section of the course will help you set logic with each of these conditional statements.
Just like conditional statements, loops in Python are vital to know. Looping refers to the execution of repeated statements until a specific condition is met. This programming language mainly uses while and for loop commands. You will learn them in this section, along with the use of break, continue, and pass statements and the use of the range function.
Python List and Dictionaries comprehension offers shorter syntax to create new lists or new dictionaries depending on the value of an existing list. This section will define why list comprehension is used and the syntax for list comprehension and dict comprehension.
Functions within a Python program are a collection or block of code that is executed only when you call for them, and they return data as a result. This segment of the Python course will teach you about creating and calling functions, along with different arguments, global and local variables, and recursion.
Python’s anonymous functions refer to those that have no name and can be invoked immediately or stored within a variable. These are known as lambda functions. They can take any number of arguments and only one expression. You will learn about them in depth in this portion.
Generators in Python allow coders to declare a function that acts like an iterator. These are the shortcuts to creating iterators, and this part of the course will teach you how to create and use generators.
Modules are similar to a code library that consists of Python definitions and statements and can be imported into other modules or to the main module. You will learn how to create modules, import functions and variables from different modules, and learn the in-built Python modules here.
Data analysis refers to inspecting, cleaning, transforming and modelling data to discover useful information and support decision-making. In this process, you can use multiple Python packages like NumPy, Pandas, and Matplotlib library functions. This section will teach you how to create packages, import modules from such packages, and the workings of NumPy, Pandas, and Matplotlib.
When your Python program encounters an error or exception while executing a code, it normally stops execution and generates an error message. You need to know ways of handling such errors and exceptions. This part of the course will teach with the necessary measures using try, except, and finally block, along with teaching multiple syntax and logical errors.
As Python programming is object-oriented, there is an object in almost everything in Python. So, you need to know what an object is and how to create it. Along with that, you must know about classes that act like object constructors in Python. This portion of the course will give you a clear view of both classes and objects, along with attributes and methods, inheritance, polymorphism, and operator overloading.
Date and time are modules of Python and are named the DateTime module, which supplies Python classes to work with date and time. You can learn multiple other associated things like time delta, strftime(), striptime() and more, along with date and time modules.
Regular Expression (Regex), a tiny but highly specialised programming language, is used within Python and is available through the “re” module. This portion of the course will allow you to understand in depth the use of regex and a few “re” module functions that are commonly used while coding.
A file in Python is the named location where you can store data. There are multiple functions in Python for creating, reading, deleting, and updating files. You can learn them from this part of the course that gives you a clear understanding of files, from opening and reading to writing and closing files.
Web Scraping is a vital skill for anyone, especially data scientists, who are responsible for analysing large volumes of datasets. This process uses an algorithm or a program to extract a huge volume of data from the web. You can learn the basics of web scraping with beautiful soup and scraping dynamic websites in this segment.
You can use Python in database applications, and this section teaches you MySQL which is one of the most popular databases. It will cover the basics of creating tables and inserting values into them, along with the idea of querying and updating and deleting database tables.
Data analysis is a process of collecting, transforming, and organising data to make data-driven decisions. In Python, data analysis can be done using NumPy and Pandas. This section will teach you data analysis and data visualisation in Python.
Python APIs are used to retrieve data from multiple sources. For example, you can retrieve weather data from various websites, and this segment will give you hands-on experience on it. Learners will get a clear understanding of APIs and how to access Public APIs.
Flask is a popular Python API that allows experts to build web applications. Python 2.6 and higher variants must install Flask, and you can import Flask on any Python IDE from the Flask package. This section of the course will help you install Flask and learn how to use the Python Flask Framework.
Lessons:
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