PYTHON COURSE

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PYTHON COURSE

PYTHON COURSE OVERVIEW

Python Course will help delegates learn how to work with and manipulate strings, perform math operations, work with Python sequences, collect user input and output results, flow control processing, write to and read from files, write functions, handle exceptions, and work with dates and times. Python is used worldwide to extract insights from their data and gain a competitive advantage. This course, in contrast to other Python tutorials, focuses on Python specifically for data science. In our Introduction to Python course, you will discover practical methods for manipulating and storing data and use data science tools to start performing your analyses.

Delegates with prior programming experience will learn to programme in Python in this live, instructor-led training course. Participants will learn how Python works and where it fits in programming languages.

Leadpoint Development training will broaden your knowledge of Python in this course, along with good programming practices. You’ll discover how to represent and store data using Python data types and variables, as well as how to direct the flow of your programmes with conditionals and loops. To keep groups of related data, you’ll use sophisticated data structures like lists, sets, dictionaries, and tuples. You’ll create custom functions, define and document them, write scripts, and deal with errors. Finally, you’ll discover how to use the Python Standard Library and other external libraries’ modules.

PYTHON COURSE LEARNING OUTCOME

  • Declare and operate on simple data types such as strings, numbers, and dates.
  • Declare and manipulate data structures such as lists, ranges, tuples, dictionaries, and sets.
  • Create loops and conditional statements.
  • Functions, classes, and modules must be defined and used.
  • Code is used to manage files and directories.
  • Handle exceptions.
  • Recognise fundamental programming concepts and Python language features.
  • Data structures, conditionals, loops, variables, and functions are among the fundamental programming concepts taught and applied.
  • To write and run Python code, use a variety of tools.
  • Create fully functional Python programmes using commonly used data structures, custom functions, and file reading and writing.

COURSE BENEFITS

Organisational Benefits.

  • It is a general-purpose programming language.
  • Rapid growth and higher production
  • A dependable community.
  • Its extensive capabilities enable developers to connect with marketplaces and exhibit their gadgets.
  • It shows to be an excellent solution for organisations concerned with data security.
  • It ensures a positive development experience, as well as user happiness.

Personal Benefits.

  • It is agile by design.
  • It enables you to code rapidly and gets from concept to implementation in record time.
  • It’s excellent for web development.
  • It is at the cutting edge of AI and Machine Learning.
  • It is an excellent way to increase your earnings.
  • It includes modules for tasks like HTTP, XML, and efficient computation handling, which are essential in developing security software.
  • It is an excellent programming language for testing concepts.
  • It includes one of the most comprehensive Machine Learning and Data Science Libraries, including TensorFlow, Scikit-Learn, Keras, Pandas, and others.
  • It assists you in being more diverse, marketable, and employable.

WHO SHOULD ATTEND?

Individuals who are new to the Python language and who already have experience with other programming languages. Python should be learned by individuals, developers, data scientists, and software engineers. Python is also for those who have never written a line of code before; they may learn Python programming. Because of its adaptability, flexibility, and object-oriented characteristics.

Vital Python – Math

Strings

Conditionals

and Loops

1
Vital Python
2
Numbers: Operations, Types, and Variables
3
To Open a Jupyter Notebook
4
Python as a Calculator
5
Standard Math Operations
6
Basic Math Operations
7
Order of Operations
8
Spacing in Python
9
Number Types: Integers and Floats
10
Complex Number Types
11
Errors in Python

Variables

1
Variable Assignment
2
Changing Types
3
Reassigning Variables in Terms of Themselves
4
Variable Names
5
Multiple Variables
6
Comments
7
Docstrings
8
Theorem in Python

Strings: Concatenation

Methods

and input()

1
String Syntax
2
Escape Sequences with Quotes
3
Multi-Line Strings
4
The print() Function
5
String Operations and Concatenation
6
String Interpolation
7
Comma Separators
8
Format
9
The len() Function
10
String Methods
11
Casting
12
The input() Function
13
String Indexing and Slicing
14
Indexing
15
Slicing

Strings and Their Methods

1
Booleans and Conditionals
2
Booleans
3
Logical Operators
4
Comparison Operators
5
Comparing Strings
6
Conditionals
7
The if Syntax
8
Indentation
9
if else
10
The elif Statement
11
Loops
12
The while Loops
13
An Infinite Loop
14
break
15
Programs
16
The for Loop
17
The continue Keyword

Python Structures

1
The Power of Lists
2
List Methods
3
Accessing an Item from a List
4
Adding an Item to a List
5
Dictionary Keys and Values
6
a List and a Dictionary
7
Zipping and Unzipping Dictionaries Using zip()
8
Dictionary Methods
9
Tuples
10
A Survey of Sets
11
Set Operations
12
Choosing Types

Executing Python – Programs

1
Algorithms, and Functions
2
Introduction
3
Python Scripts and Modules
4
Shebangs in Ubuntu
5
Docstrings
6
Imports
7
The if __name__ == “__main__” Statement
8
Basic Functions
9
Positional Arguments
10
Keyword Arguments
11
Iterative Functions
12
Exiting Early
13
Activity 10: The Fibonacci Function with an Iteration
14
Helper Functions
15
Don’t Repeat Yourself
16
Variable Scope
17
Variables
18
Defining inside versus outside a Function
19
The Global Keyword
20
The Nonlocal Keyword
21
Lambda Functions
22
Mapping with Lambda Functions
23
Filtering with Lambda Functions
24
Sorting with Lambda Functions

Extending Python

Files

Errors

and Graphs

1
Reading Files
2
Writing Files
3
the Date and Time in a Text File
Python is a programming language emphasising readability, making it simpler to comprehend and use, and may thus be seen as beginner-friendly. Furthermore, because its syntax resembles the English language, it is simple for new programmers to enter the programming field. Moreover, the rules aren't rigidly established in Python since it is a flexible, dynamically typed language, which makes it easier to understand. Additionally, it is a more tolerant language that can function with some degree of fault. The simplicity of use was one of Guido van Rossum's foundational ideals when he developed Python in 1989. It is also adaptable. It is open-source software that can function on many different operating systems, including Windows, Linux, and Mac OS. Python is an excellent language for beginners since its readability and other structural components are designed to be simple to comprehend. The fundamentals of Python are also straightforward to master. However, Python is not only for simple tasks. Some of the world's most intricate websites and applications are supported by it. Python supports both a procedural-oriented programming language and all the characteristics of an object-oriented programming language. Python's popularity among developers, data scientists, and software engineers is no coincidence.
Yes, you can begin studying Python independently due to its relative simplicity. Installing the language and using it from any location on your computer is quite simple. In addition, there is a sizable and active user community for Python, so it's simple to locate someone who can help if you run into issues. Many aspiring Python developers are enrolling in Python courses to speed up their learning. Python Programming certificate programme enables you to learn the fundamentals of Python from knowledgeable industry professionals and gain practical experience writing lines of code. Not just for beginner Python Developers, coding boot camps and data science courses have grown in popularity as a learning option for people looking to learn Python. As with professionals in other tech fields, Python experts must continue learning to keep up with advancements in programming languages, methodologies, and data science trends.
You would need to dedicate a full-time schedule to studying Python if you're a beginner and want to master it in less than two months. It can take roughly 250 hours to properly build your Python abilities if you put in 40 hours per week of study. Most beginners interested in learning Python create a schedule where they allocate a specific number of hours per day to studying the language's foundations and another period of time each day to practise what they have learned.
Yes, learning Python will pay off since Python-savvy programmers are in high demand in some of the trendiest technological disciplines, such as machine learning and artificial intelligence. Python is the preferred language across various industries, including data science, data analysis, and machine learning, thanks to well-known ML packages like Pandas and Scikit-learn. It is significant since there is a rising need for workers with ML expertise, with ML employment expected to be valued at $31 billion by 2024. Python can be helpful for a variety of professional categories due to its adaptability and the various functions and applications it has. But if your work involves software, the web, data, products, or design, you should at least master the fundamentals.
Python does not require any prior knowledge of mathematics. The fact is that you could learn Python with absolutely no mathematical skill at all. However, it does assist in having a high school-level grasp of algebra. Recent research revealed that communication abilities are significantly more crucial than math in coding, and recruiting processes should consider this.
Knowing Python can undoubtedly help you acquire a job, but it is only one factor to consider, along with your work experience, skill set, and educational background. Employers appear to favour Python programming abilities across a wide range of sectors.
Yes, no prior programming experience is necessary to learn Python. Python's popularity stems in part from its simplicity and intuitiveness. Python is the ideal programming language for beginners with no coding knowledge. Python code is as straightforward to understand as English instructions.

Among programmers, Python is a popular language for data scientists, software engineers, and even hackers due to its versatility, flexibility, and object-oriented features. Python's numerous libraries, frameworks, vast collections of modules, and file extensions are responsible for many of the web and mobile applications we use today. Not only that, but Python is excellent for developing micro-project to macro-enterprise web services, as well as supporting other types of programming languages.

Despite being a high-level language capable of performing complex tasks, Python is simple to learn and has a straightforward syntax. As a result, it is appropriate for both novice and experienced programmers. 

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Enrolled: 16 students
Duration: 3 DAYS
Lectures: 90
Video: 10 hours
Level: Intermediate

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Working hours

Monday 9:30 am - 6.00 pm
Tuesday 9:30 am - 6.00 pm
Wednesday 9:30 am - 6.00 pm
Thursday 9:30 am - 6.00 pm
Friday 9:30 am - 5.00 pm
Saturday Closed
Sunday Closed